Flood risk assessments

Useful for

Use cases llm-inferred

Nearest-gauge river level and flow context for FRA baseline · Check live flood warnings and alerts for a site's catchment · Pull recent level and flow readings for hydrological baseline review · Locate monitoring stations within a set radius of a project site

Audience llm-inferred

flood consultants · hydrologists · drainage engineers

Limitations

Constraints docs-verified

No service level guarantee; not suitable for safety-critical applications · Upstream Environment Agency API is Beta · Responses may be cached for short periods · List tools capped at 500 items (default 50; readings default 100), 60 KB truncation; use limit/offset to paginate · Coverage conflict: docs say UK, ENTRY metadata says England

Useful for

Use cases llm-inferred

FRA baseline flows from nearest gauge: find sites by bbox, then pull daily mean discharge (00060) for the baseline period · Current conditions check at gauges during a flood or drought review, using percentile ranking as indicative only · Groundwater depth baseline from monitoring wells via parameter 72019 · Monitoring site inventory for a catchment by HUC code, filtered to sites with instantaneous data

Audience llm-inferred

hydrologists · flood risk consultants · drainage engineers · GIS analysts · ecologists (groundwater and surface water baselines)

Limitations

Constraints llm-inferred

Covers US and territories only; no UK data · Percentile ranking is approximate and is not a flood-stage or drought determination · Readings return up to 100 sites per call, with at most 100 series and the 10 most recent records per series · Series inline output is capped at 500 records; larger results need CANVAS_PROVIDER_TYPE=duckdb · Dataframe tools and spillover require CANVAS_PROVIDER_TYPE=duckdb; table drop is opt-in via WATER_DATAFRAME_DROP_ENABLED · Pre-1.0 release (v0.3.0), so the interface may change · Relies on the USGS NWIS service being available; upstream failures are returned as retryable errors · Public hosted endpoint is not operated by USGS and has no stated uptime guarantee

Useful for

Use cases llm-inferred

FRA baseline flows: find gauges within a buffered site polygon with hydro_find_gages and read drainage area (dasqmi) and NWIS linkage · Drainage strategy context: identify the HUC12 watershed and its downstream HUC for a site with hydro_identify_watershed · Watercourse and waterbody constraint mapping for planning or ecological screening using hydro_find_waterways and hydro_find_waterbodies · Outfall and culvert screening using modelled EROM flow and velocity from flowline attributes

Audience llm-inferred

flood consultants · hydrologists · drainage engineers · GIS analysts · ecologists · planners

Limitations

Constraints docs-verified

Each layer caps at 2000 records per request; results set truncated: true when the cap is hit · Feature geometry is not returned, so results are attributes only · Tools are geometry-intersection queries; routed upstream/downstream tracing is not yet implemented · Drainage-area units differ: gages use square miles (dasqmi), flowlines and watersheds use square km · Point and line layers need a Polygon or BoundingBox to reliably capture features · Covers the United States only

Useful for

Use cases llm-inferred

Hydrology baseline from nearest Swiss gauging station (levels, flows) for water-resource projects · Air quality baseline check against Swiss LRV and WHO 2021 limits for EIA screening · Aircraft noise screening of planning sites using LV95 coordinates · Natural hazard screening (flood, avalanche, wildfire) in site due diligence

Audience llm-inferred

hydrologists · environmental consultants · planners · GIS analysts

Limitations

Constraints docs-verified

Swiss data only; not applicable to UK sites · Hydro station search has no canton filter; flood warnings are nationwide with no canton filter · env_hydro_history returns latest value plus an access path for real-time series, not full series · Aircraft noise contours are isolines: results are a dB bracket/upper bound, orientation aid only, not legally binding · Coordinates must be LV95 (EPSG:2056); WGS84 input is rejected · Hazard overview/regions tools are routers only; the naturgefahren.ch aggregate API was discontinued · Per-query caps apply and each API call times out after 30 seconds · Subject to upstream terms of service (BAFU, hydrodaten.admin.ch, naturgefahren.ch, waldbrandgefahr.ch) · Requires Python 3.11+ for local install · Tool budget is declared exhausted (21 tools); metadata lists tools as empty

Useful for

Use cases llm-inferred

Catchment land cover and forest cover percentage for flood risk assessment inputs · Flood extent area from imagery using threshold_area for post-event mapping · NDVI/NDWI change between periods via multi_period_analysis for ecological baselines · Zonal statistics of DEM or land cover over a catchment for morphometry

Audience llm-inferred

GIS analysts · hydrologists · flood consultants · ecologists · environmental consultants using AI-assisted workflows

Limitations

Constraints docs-verified

Requires Google Earth Engine authentication and a GEE project ID · AI code-generation tools need an LLM provider API key · Local install required (Poetry, clone repo); Python 3.11 to 3.14 · Catalogue auth field lists only LLM keys and omits GEE credentials · AI-generated GEE code and factuality outputs need expert verification · No rate limits, SLA or maintenance status stated in docs

Useful for

Use cases llm-inferred

Historical daily PRCP and TMAX/TMIN series from the nearest GHCND station for a US project climate baseline · Storm Events flood and hail records for a US state and year as hazard evidence in a risk assessment · Billion-Dollar Disaster cost and frequency context for resilience or adaptation reporting · Screen station data-coverage dates before fetching observations for a US hydrology or drainage study

Audience llm-inferred

hydrologists · climate risk analysts · civils engineers on US projects · GIS analysts · planners

Limitations

Constraints llm-inferred

Data is US-focused (ENTRY regions: United States; docs reference US states and NCEI corpora), so it has limited use for UK projects · Requires a free NOAA CDO token for CDO tools · CDO fetch_data span caps: 1 year for GHCND and PRECIP/NEXRAD/NORMAL daily-hourly datasets, 10 years for GSOM, GSOY, NORMAL_MLY, NORMAL_ANN · GHCND values are raw tenths-of-unit integers unless units is set to metric or standard · Storm Events limited to one year per query, and fails for years NCEI does not publish · Billion-Dollar Disasters coverage ends at the last year NCEI has finished assessing · Public hosted endpoint is third-party and not guaranteed; self-hosting adds maintenance · No CDO rate limits stated in docs

Useful for

Use cases llm-inferred

ERA5 rainfall and temperature history (weather_archive) for FRA or drainage baseline climatology · Forecast rainfall and wind for construction-phase site planning · GloFAS river discharge screening (flood_forecast) at site coordinates before gauge data review · CMIP6 climate projections (climate_projection) for climate-change allowances in drainage strategy

Audience llm-inferred

flood consultants · drainage engineers · hydrologists · planners · GIS analysts

Limitations

Constraints llm-inferred

Docs cover free use for non-commercial purposes only; commercial consultancy use must be checked against Open-Meteo terms · ENTRY auth lists API_KEY, but the docs say no key is needed for Open-Meteo; API_KEY only protects HTTP mode · Model-specific tools are regional (ICON for Germany/Europe, MET Norway for Nordic countries); UK coverage is not named · GloFAS flood discharge is modelled, not gauge observations · Responses over 25,000 characters are truncated; narrow the date range or variables to get full data · Response cache is in-memory only and not persistent · Archive ranges ending within the last 5 days are still being backfilled by Open-Meteo · Tool argument names in example_tool_calls are inferred from Open-Meteo API conventions, not from DOCS · Docs give no maintenance or release-status information

Useful for

Use cases llm-inferred

Find Sentinel-2 or Landsat scenes over a UK catchment bbox for pre- and post-flood imagery · Estimate download size of satellite tiles before pulling data for a BNG habitat baseline · Locate DEM or land-cover STAC collections for drainage strategy catchment analysis, where the target catalog hosts them

Audience llm-inferred

GIS analysts · flood consultants · hydrologists · ecologists · drainage engineers

Limitations

Constraints llm-inferred

Results depend entirely on the STAC catalog queried; no catalog is bundled · get_queryables returns an empty set if the catalog does not implement the endpoint · get_aggregations returns a message rather than data if the catalog does not support aggregation · sign_assets only applies to Microsoft Planetary Computer catalogs · estimate_data_size depends on odc.stac and XArray and falls back to estimates when odc.stac fails · Install URL in DOCS (wayfinder-foundry/stac-mcp) differs from ENTRY url (BnJam/stac-mcp); confirm the source repository before use · DOCS refer to a planned FastMCP integration (issues #69, #78) that is not yet delivered · No authentication is documented, so private or authenticated STAC APIs are not covered

Useful for

Use cases llm-inferred

Check project length units and plan descriptions in existing HEC-RAS models during flood model QA · Pull selected plan metadata from HEC-RAS text files into a bounded review note for a model handover · Confirm ras-commander and ras-commander-mcp versions in a managed environment before starting modelling work

Audience llm-inferred

flood consultants · hydraulic modellers · hydrologists

Limitations

Constraints docs-verified

Read-only: does not modify projects, compute, read HDF/DSS, inspect geometry, extract gridded data, export files or download into projects · Project metadata and plan configuration need ras-commander 0.104.0; on 0.103.0 those tools return an availability error · Project tools are meant only for bounded informational subagents; other hosts need a scoped Python workflow · Only project roots listed in RAS_MCP_ALLOWED_ROOTS are readable; no roots are trusted by default · Claude Code plugin is forthcoming and its repository is not yet published · Version 0.4 replaces the 0.3 tool set and needs migration · Windows: other tools in a workflow may still fail on paths over 260 characters · Independent project, not affiliated with or endorsed by USACE HEC

Useful for

Use cases llm-inferred

Automate loading site, catchment and boundary layers, checking CRS and zooming to extents for flood or drainage report figures · Run zonal statistics and raster sampling on DEM or rainfall rasters to prepare drainage strategy inputs · Apply styled, labelled layers and layouts to produce BNG habitat baseline maps

Audience llm-inferred

GIS analysts · flood consultants · drainage engineers · ecologists · planners

Limitations

Constraints docs-verified

Needs a running QGIS desktop session with the plugin's server started; it is not a standalone data source · Plugin (inside QGIS) and MCP server (outside QGIS) must be kept in version sync · uvx caches the server archive, so updates need a forced refresh; auto-update requires network at launch

Useful for

Use cases llm-inferred

Nearest river-level and flow gauge lookup for FRA baseline flow context · Historic level and flow readings via startdate/enddate for hydrological model calibration · Flood warning and flood area screening within a radius of a site (lat/long/dist filter) · Latest rainfall and level readings as a context check for drainage strategy studies

Audience llm-inferred

flood consultants · hydrologists · drainage engineers · GIS analysts · civils engineers

Limitations

Constraints docs-verified

Labelled a trial/beta service; feedback requested · No service-level guarantee; should not be relied on for safety-critical applications · Does not replace the Agency's official channels for notifying the public of floods · Responses may be redirected at high load or in future versions; clients must follow standard HTTP redirects · Responses may be cached briefly; custom filtering reduces cache hits · Readings are sometimes updated in batches, so a complete history needs the since filter · Some endpoints impose a length limit by default; check the metadata limit and offset values · No rate limit documented; the docs recommend one call every 15 minutes (data/readings?latest) rather than crawling every station

Useful for

Use cases llm-inferred

FRA baseline flows and levels from nearest gauge · Rainfall and river level context for flood event review · Groundwater level baseline for site investigation or geotechnical assessment · Water quality baseline (dissolved oxygen, turbidity, nitrate) for ecological or pollution assessment

Audience llm-inferred

flood consultants · hydrologists · drainage engineers · ecologists · geotechnical engineers · GIS analysts

Limitations

Constraints docs-verified

Hard limit of 2,000,000 rows per call that cannot be overridden; soft limit of 100,000 rows per call (overridable with _limit) · Hard limit is subject to review and may be reduced if the service is overloaded · Bulk downloads should use the batch API; otherwise keep to one non-batch request in flight at a time · Concurrency limits may be enforced per IP address, and excessive demand may lead to blocking · Logged groundwater sub-daily values may mix 15-min and hourly intervals · Station identifiers are not always unique; some stations need a composite key with a wiskiID · HTML views are intended for debugging and development, not for presentation to consumers

Useful for

Use cases llm-inferred

Baseline river flow and gauge record review for FRA inputs from nearest USGS gauge (US sites only) · Flood event analysis from continuous sensor records at gauged catchments · Water quality baseline sampling review for environmental assessment (US sites only) · Gauge camera imagery for site visit verification and condition checks

Audience llm-inferred

flood consultants · hydrologists · GIS analysts · environmental scientists · water quality specialists

Limitations

Constraints llm-inferred

Covers United States monitoring locations only; not applicable to UK sites · Rate limits apply without an API key · Licence not specified in catalogue metadata · Multiple API families (OGC, STAC, legacy Water Services, NIMS) may require different query patterns · NIMS imagery requires constructing full image URLs from camera base paths and returned filenames

Useful for

Use cases llm-inferred

Catchment terrain and slope analysis for an FRA study area from a bbox DEM · Topographic levels for drainage strategy and earthworks setting-out inputs · Terrain base layer for GIS site analysis

Audience llm-inferred

GIS analysts · hydrologists · drainage engineers · civils engineers

Limitations

Constraints llm-inferred

Licence varies by dataset · API key required · No docs retrieved, so capabilities and coverage are unverified

Useful for

Use cases llm-inferred

Flood extent mapping from Sentinel-1 SAR imagery to support FRA evidence · Pre- and post-event change detection for site screening and geotechnical or landslide review · Vegetation index time series from Sentinel-2 for BNG habitat baseline mapping

Audience llm-inferred

GIS analysts · hydrologists · ecologists · geotechnical engineers

Limitations

Constraints llm-inferred

Quotas and limitations depend on user type and plan · No UK-specific coverage or update cadence stated in the docs · Use is governed by the Copernicus licence

Useful for

Use cases llm-inferred

Flood screening for a site in a transboundary or large catchment · Regional context for an FRA desk study · Checking global flood awareness signals alongside local gauge data

Audience llm-inferred

flood consultants · hydrologists

Limitations

Constraints llm-inferred

No DOCS retrieved, so capabilities, resolution, formats and update cadence are unverified · Copernicus licence terms need checking before reuse in client deliverables

Useful for

Use cases llm-inferred

FRA catchment context: delineate contributing catchment boundaries from HydroSHEDS basins · Drainage strategy: river network and lake layers for receiving-watercourse context · Ecology/BNG baseline: river and lake network mapping for habitat context

Audience llm-inferred

hydrologists · flood consultants · drainage engineers · GIS analysts · ecologists

Limitations

Constraints docs-verified

HydroSHEDS v2 is released for the Americas; the global v2 (TanDEM-X based) is still in development · Specific resolutions, update cadence and licence terms are not stated in DOCS

Useful for

Use cases llm-inferred

Flood risk assessment: ground-level inputs for hydraulic model topography · Drainage strategy: surface levels for catchment and overland flow delineation · Civils design: existing ground model for earthworks and levels

Audience llm-inferred

flood consultants · drainage engineers · hydrologists · GIS analysts · civils engineers

Limitations

Constraints llm-inferred

No docs retrieved, so coverage, formats, resolution and access terms are unverified · Auth and licence not recorded in entry

Useful for

Use cases llm-inferred

Forecast rainfall and temperature context for construction programme weather-risk reviews · Qualitative forecast precipitation and runoff context for flood-event briefings (not a substitute for design rainfall) · Wind and significant wave height forecast context for coastal and marine works planning · Forecast soil moisture and temperature as context for earthworks and ground-condition risk notes

Audience llm-inferred

hydrologists · flood consultants · coastal engineers · civils planners and programme managers · GIS analysts and data engineers

Limitations

Constraints llm-inferred

0.25 degree resolution only; higher-resolution products need a Real-time Dissemination Service Agreement · Rolling archive of 12 runs (about 2-3 days); full historical archive requires a service agreement · Limit of 500 simultaneous connections to the Open-Data Portal · Some parameters currently unavailable (t20d depth of 20C isotherm; sav300 average salinity), per the docs as of Aug 2026 · Stream names changed from 06z/18z scda/scwv to oper/wave from IFS Cycle 50r1; parameter lists may change · Not a design-rainfall dataset; forecasts only, no observed or historical series · Service Charges may apply to some access routes

Useful for

Use cases llm-inferred

Coastal flood baseline: tidal range and extreme water levels from nearest station using verified high/low and daily max/min data · Tidal boundary conditions for coastal or estuarine flood models using 6-minute water levels and predictions · Long-term sea-level and datum context using verified monthly mean and daily mean water levels · Tidal current inputs for estuarine outfall or marine works design using currents_predictions

Audience llm-inferred

flood consultants · coastal engineers · hydrologists · marine and civils engineers

Limitations

Constraints llm-inferred

US stations only per ENTRY regions; not applicable to UK sites · Datum is mandatory for water level products, so every request must specify one · Per-request length limits: 1-minute 4 days; 6-minute 1 month; hourly and high/low 1 year; daily means and daily max/min 10 years; monthly means 200 years · Verified data is released station by station each month, with no specific date per station · Each verified interval is a separate product and cannot be selected with the interval parameter · Bin number is required for most current stations · Subordinate tide-prediction stations support only high/low intervals · Datums product is no longer available on this API; use the Metadata API · No auth or licence stated in ENTRY; check terms before commercial use

Useful for

Use cases llm-inferred

Pre-acquisition screening of a site for flood, radon and zoning constraints · Planning-context scoping: nearby planning applications and zoning for a site appraisal · Sold-price context for a residential property in a feasibility or due-diligence note · Recorded-crime and BER area context as background in a property due-diligence brief

Audience llm-inferred

environmental consultants · flood risk consultants · planning consultants · property due-diligence analysts · GIS analysts

Limitations

Constraints docs-verified

Returns records only; not a valuation engine · Eircode-only lookup is not supported; an address or rough location is needed · River and coastal flood models are not included (licence-restricted; check floodinfo.ie) · Zoning is generalised land-use zoning (Myplan), not a detailed parcel-level designation · Recorded crime is area-level CSO counts, not incidents at an address; homicide and sexual offences are not published at sub-district level · Early release (v0.2.0); post-launch reliability and upstream-drift detection are active priorities · Requires Node.js 20+; running npx alone waits for an MCP client and appears to hang

Useful for

Use cases llm-inferred

Flood zone, permit and code-case screening for a site due-diligence note · Zoning, lot dimensions and municipal code text lookup for a pre-application brief · Tree-permit and roadway work-zone check before site clearance or access planning · Special-district (MUD/PID) and appraisal context for a development or drainage-authority brief

Audience llm-inferred

flood consultants · planners · civils engineers · GIS analysts

Limitations

Constraints llm-inferred

Austin, Texas and Travis, Williamson and Hays counties only; no UK data, so relevance to a UK consultancy is low, although the catalogue lists regions as Global · Early-stage project run by a single maintainer, so expect gaps and possible breaking changes · MLS data covers active and under-contract listings only, with no sold comps · Listings, neighbourhood and blog content depend on neuhausre.com and the Neuhaus VOW API · Socrata rate limits apply unless an app token is set · Commute tool uses demo routing servers with no real-time traffic · Catalogue auth field says an API key is required, but docs say no key is needed · Catalogue tool list does not match docs: docs state 43 tools and list austin_utility_providers, austin_relocation, austin_local_voices and austin_health, which are absent from the metadata, while the metadata lists health_check

Useful for

Use cases llm-inferred

Locate a C# class or symbol definition in a large .NET codebase without grep flooding the context · Find string references to a symbol before a change using search_text (not semantic find-usages) · Rename a C# symbol across a project with rename_refactoring instead of sed

Audience llm-inferred

software developers using JetBrains Rider on C#/.NET codebases · game developers working on large Unreal C++ projects

Limitations

Constraints llm-inferred

Not a water, civils or environmental data source; it is a developer code-navigation tool · Requires Rider running with its MCP server connected · No semantic find-usages/find-references tool; reference search is indexed string match · search_symbol on Unreal C++ can return filename or path matches instead of the exact class · Results are capped at the top N (RIDER_MAX_RESULTS), so output is not exhaustive · Rider's index excludes Saved/ (logs, build output), so log paths return empty results · rider_regen_project auto-detect is Windows-only, and Rider must reload the solution after regen

Useful for

Use cases llm-inferred

Preliminary flood-safety screening of California or Texas sites during US development due diligence · Air quality and noise context for site-selection notes covering CA or TX addresses · Neighbourhood walkability and industrial-proximity baseline for US planning reports

Audience llm-inferred

developers building AI neighbourhood-analysis agents · US-focused GIS analysts · US planners and real estate analysts

Limitations

Constraints docs-verified

Coverage limited to California and Texas, so no UK data · Fire risk covers California only · Requires a paid API AI Pro plan and an iHuus API key · Catalogue regions field says Global, which conflicts with the docs' CA/TX coverage · Repository does not accept external pull requests, a maintenance risk

Useful for

Use cases llm-inferred

Flood-zone screening for a DFW site address using dfw_fema_flood, with insurance interpretation · Development watch on a site: permits and code-compliance cases in Fort Worth, McKinney or Arlington · Utility provider identification (water/sewer PUC CCN) for a Texas site during due diligence · Council district, county and ISD lookup for a site to support planning and stakeholder mapping

Audience llm-inferred

flood risk consultants · planners · land and property due-diligence consultants · GIS analysts

Limitations

Constraints docs-verified

Covers Dallas-Fort Worth, Texas only; no UK data (entry regions field says Global, which the docs do not support) · Dallas permits and code cases are not wired (stale feeds; code-case publication stalled 2025-01-31) · Irving and other suburbs beyond Fort Worth, McKinney, Arlington, Denton and Dallas are not covered; composed property tool is pending · Not for tenant, employment, credit, insurance or other FCRA-regulated screening · Appraisal values are the 2025 certified appraised value, not a tax bill; only 4 core counties verified · Events from Ticketmaster require a free API key; some suburbs publish no usable calendar · Requires Node 20 or later · Upstream free text (311, events) is untrusted and treated as data

Useful for

Use cases llm-inferred

Pull 7-day stream flow and gage height for a gauged US river reach as hydrology inputs · Locate USGS monitoring stations within a project bounding box for baseline data review · Check currently flooding reference points as context for US flood-impact comparisons

Audience llm-inferred

hydrologists · flood consultants · GIS analysts · environmental scientists

Limitations

Constraints llm-inferred

US-only data (USGS network and US state codes); not applicable to UK catchments · USGS API has usage limits; avoid rapid repeated requests · Some sites may have no data for the requested period or parameters · Requires local Python install (pip install -e . or httpx and mcp) and Claude Desktop config · current_water_levels.py is a deprecated legacy file

Useful for

Use cases llm-inferred

FRA baseline weather and river-level context for a GB site, using Environment Agency gauge levels against typical range · Historical weather review back to 1940 for drainage or flood event investigations · Forecast, lightning and alert checks to support site visit and fieldwork planning · Air quality and pollen checks for ecological or construction site work in Europe

Audience llm-inferred

flood consultants · hydrologists · drainage engineers · environmental consultants

Limitations

Constraints docs-verified

Some tools are US-only · Free public APIs come with fair-use rate limits · Minutely precipitation nowcast only in North America and Central Europe

Useful for

Use cases llm-inferred

FRA screening: modelled GloFAS river discharge baseline at site coordinates (no gauge data) · Climate change context for drainage design: CMIP6 daily projections for 2050 horizons · Site terrain screening: Copernicus DEM elevation at point coordinates for earthworks and drainage routing · Open-coast scheme inputs: wave height and swell conditions

Audience llm-inferred

flood consultants · hydrologists · drainage engineers · civils engineers · climate resilience consultants · GIS analysts

Limitations

Constraints llm-inferred

Global dataset; DOCS describe no UK-specific sources or validation · Air quality is modelled grid data, not station measurements · Pollen is modelled for Europe only, and only in pollen season · River discharge comes from the largest modelled river within 5 km, not always the nearest; null outside GloFAS coverage · cerra covers Europe only; regional models queried outside coverage fail · ERA5-family historical data runs about 5 days behind; ecmwf_ifs has no delay · Marine: sheltered water returns near-zero waves; land points return nulls · Climate projections are daily-only · Elevation is a ~90 m DEM, not survey-grade · Upstream rate limits fail as rate_limited · Large results spill to a DuckDB canvas only when CANVAS_PROVIDER_TYPE=duckdb · Auth mode unverified in DOCS

Useful for

Use cases llm-inferred

Canadian hydrometric flow and flood-risk context for a flood risk assessment on a Canadian site · Canadian climate and rainfall normals as inputs to drainage design on Canadian projects · Discovering Canadian open geospatial datasets (CKAN, ArcGIS Hub, WFS) for desk-based site baselines · Canadian exchange-rate or commodity price inputs for project costing

Audience llm-inferred

hydrologists · flood consultants · GIS analysts · environmental consultants working on Canadian projects

Limitations

Constraints llm-inferred

Canada-only data; no UK coverage, so of limited use for terramcp.earth's UK-focused work · Entry description states 266 tools, but DOCS state 295 tools · Depends on many upstream government APIs whose availability and rate limits are outside the server's control · Requires Python 3.12+ and uvx to run · No spatial or temporal resolution or update frequency documented

Useful for

Use cases llm-inferred

Current and forecast weather context for site visit or fieldwork planning · Weather inputs for construction work-day scheduling notes · Rainfall and temperature context for drainage or flood-risk briefing notes

Audience llm-inferred

drainage engineers · hydrologists · civils engineers · planners

Limitations

Constraints llm-inferred

README does not describe the weather data fields, historical depth, spatial resolution or update frequency · Requires a personal QWeather API key set in a config file (hefeng.api.key) · ENTRY says no credentials are documented, but README requires an API key · No tools are listed in the metadata and the README names none · UK coverage is not documented; QWeather terms, quotas and availability are outside this repo · Single-author third-party wrapper with no stated maintenance commitment

Useful for

Use cases llm-inferred

Site visit planning: current conditions and 5-day forecast for survey or inspection days · Recent weather context for flood or incident reports using the last 5 days of historical data · Air quality screening for dust or construction monitoring sites via get_air_quality · Weather alert checks for construction programme and works-risk reviews

Audience llm-inferred

environmental consultants · civils engineers · site engineers · project managers

Limitations

Constraints docs-verified

New API keys may take up to 24 hours to activate · Free tier limited to 60 calls per minute and may be throttled during heavy use · Historical data limited to the last 5 days · Forecast limited to 5 days · Requires Python 3.10+ and a locally running server process while using Claude Desktop · Setup instructions use Windows-style paths and the py launcher · Tools list in catalogue metadata is empty, although docs list six tools

Useful for

Use cases llm-inferred

Short-range (36-hour) weather context for site visits and fieldwork scheduling on Taiwan projects · Weather briefing for site walkovers and drainage or flood inspections in Taiwan · Quick county-level forecast lookup to support construction programme risk notes for Taiwan sites

Audience llm-inferred

environmental consultants · civils engineers working on Taiwan projects · site managers · planners

Limitations

Constraints llm-inferred

Unofficial server, not affiliated with the Central Weather Administration (CWA) · Forecast tool only: no observations, radar, or longer-range forecasts in the documented feature set · Requires a CWA API key · Taiwan only, with no UK coverage · Windows npx launch can fail; docs give cmd or node workarounds

Useful for

Use cases llm-inferred

Catchment area and centroid calculation from boundary files (read_file_gpd, get_area, get_centroid) for FRA or drainage baselines · Reproject site boundaries and survey points to British National Grid (EPSG:27700) before overlay (project_geometry, reproject_raster) · Zonal statistics of DEM or rainfall rasters within catchment polygons (zonal_statistics) for drainage or flood-risk inputs · Clip and overlay habitat or constraint layers with site boundaries (clip_vector, overlay_gpd) for BNG baseline mapping

Audience llm-inferred

GIS analysts · hydrologists · flood consultants · drainage engineers · ecologists

Limitations

Constraints llm-inferred

Version 0.15.0 is beta, so the API may change · Requires Python 3.10 or higher · Google Cloud Storage backend needs the gis-mcp[gcp] extra plus credentials and IAM setup · Docs do not describe per-tool inputs, outputs, or CRS and resolution behaviour · Catalogue tool list has 59 tools with none for climate, ecology, movement or boundary data, although the docs claim 92+ tools that include those categories; confirm which tools ship · No UK-specific datasets (e.g. EA gauges, OS, DEFRA) are listed; coverage is generic GIS tooling · Data-gathering categories depend on external sources whose availability and rate limits are not documented

Useful for

Use cases llm-inferred

Batch-export layout PDFs or PNGs of constraint or flood-zone maps from an ArcGIS Pro project · QA attribute completeness on drainage or asset layers with the qa_layer recipe before issuing data · Buffer and dissolve site constraint layers for screening in an ArcGIS Pro project · Bulk-update inspection or status fields on survey points matching a query before reporting

Audience llm-inferred

GIS analysts · drainage engineers · hydrologists · planners

Limitations

Constraints docs-verified

Needs a live ArcGIS Pro 3.x session with a Map, Scene or Globe active; the bridge must be started each session · Map view must be opened manually once per session and cannot be automated · Interactive sketch-tool digitizing cannot be automated · execute_python is disabled unless the user opts in · run_geoprocessing is limited to an allowlist of toolboxes, and destructive tools are blocked · publish_web_layer needs the arcgis package and a signed-in portal session · Recipes and the socket transport need the hardening layer, which loads only when the bridge is started via the toolbox or with __file__ · Setup instructions use Windows paths

Useful for

Use cases llm-inferred

Find and repair broken layer sources across an open ArcGIS Pro project before issuing a report · Summarise attribute counts and statistics per category for a drainage or flood asset layer · Select features by location against a boundary layer and export the result for a planning or EIA report

Audience llm-inferred

GIS analysts · hydrologists · flood consultants · drainage engineers · ecologists

Limitations

Constraints llm-inferred

Requires ArcGIS Pro to be open; the MCP endpoint is served from inside Pro, so the client connection fails when Pro is closed · Requires ArcGIS Pro 3.7 or newer; will not load on older versions · Windows-only host environment (add-in and PowerShell bridge) · Arbitrary arcpy execution (execute_arcpy_code) needs an optional Python bridge inside ArcGIS Pro · Endpoints bound to 127.0.0.1, so not reachable from other machines · Tool parameter schemas are not published in the DOCS, so example arguments must be checked against the live server · Destructive tools (remove_map, delete_features, delete_field, update_features) are marked with a warning in DOCS

Useful for

Use cases llm-inferred

Slope and aspect from a site DEM for drainage or earthworks setting-out (raster_operations) · Overlay and dissolve constraint layers such as flood zones and site boundaries in a project GDB (geometry_analysis) · Hot-spot or kernel density analysis of flood or incident records (spatial_statistics) · Export PDF/PNG map plates for planning or flood risk assessment submissions (export_layout)

Audience llm-inferred

GIS analysts · drainage engineers · hydrologists · civils/BIM engineers · planners

Limitations

Constraints docs-verified

Windows only; needs a licensed ArcGIS Pro installation and its Python environment set as ARCPY_PYTHON_PATH · Automated tests use mocked arcpy; the 100 geoprocessing tools are not validated across scenarios on a licensed runtime · Ten state-mutating tools (e.g. delete_dataset, repair_geometry) refuse to run without confirm: true · Some tools need Esri Spatial or Network extension licences · Sketch-to-GIS demo is marked 'coming soon'

Useful for

Use cases llm-inferred

Inspect and repair invalid layers in an existing flood risk or drainage QGIS project, then improve cartography · Build a print layout of a site or catchment study area and visually review the rendered map before issue · Run Processing steps such as clipping or reprojection on consultancy GIS data within the open QGIS session

Audience llm-inferred

GIS analysts · flood consultants · drainage engineers · civils and BIM engineers

Limitations

Constraints llm-inferred

Requires a live QGIS Desktop session; it does not operate on data without QGIS running · Aesthetic map review needs a vision-capable AI client · Plugin recommendations exclude deprecated plugins and treat experimental plugins as opt-in · Validated on QGIS LTR 3.44.12 and QGIS 4.2 only, per the docs

Useful for

Use cases llm-inferred

Serve PostGIS drainage or flood-model layers to QGIS and ArcGIS Pro via OGC API Features or GeoServices FeatureServer · Publish survey or site investigation layers as vector tiles for client web maps · Expose PostGIS asset or monitoring data to Power BI or Excel via OData for reporting

Audience llm-inferred

GIS analysts · GIS developers · IT and DevOps teams hosting spatial data

Limitations

Constraints docs-verified

Serves data only; users must load their own layers (PostGIS required, bring your own or use the bundled compose stack) · No versioned v* release tagged yet; nightly container image is the current route · Pro and Enterprise features (e.g. FeatureServer applyEdits, service imports, OIDC SSO) need a signed license · ImageServer, OGC API Coverages and WMTS are Preview · Esri client compatibility is limited to the published parity and certification matrices

Useful for

Use cases llm-inferred

Geocode a site address to coordinates and map its location context for a site appraisal or FRA report · List schools, parking and EV charging near a development site for a site logistics or planning-context note · Compare commute and route options for site staff or sub-consultant travel to a project location · Gather neighbourhood livability and amenity context as a desk-study baseline before a site visit

Audience llm-inferred

GIS analysts · planners · civils engineers (site logistics and access)

Limitations

Constraints llm-inferred

No UK-specific coverage, data provenance or update cadence documented; catalogue lists region as Global · No time span, spatial resolution or data currency documented · Debugging is harder because the server runs over stdio · README client example uses an HTTP URL (http://localhost:8000) while the server is described as stdio, so transport setup needs checking · No rate limits or upstream OSM service terms documented · Parking, EV charging and school results depend on how features are tagged in OpenStreetMap, so completeness will vary · Tool input parameters beyond geocode_address are not documented

Useful for

Use cases llm-inferred

Japanese site screening: 用途地域 and 防火・準防火地域 checks for a development site · Flood and coastal hazard screening using 洪水浸水想定区域, 高潮浸水想定区域 and 津波浸水想定 layers · Slope and ground hazard screening using 地すべり防止地区, 急傾斜地崩壊危険区域, 大規模盛土造成地マップ and the liquefaction tendency map · Comparable transaction and land price research using 不動産価格 and 地価公示・地価調査 point data

Audience llm-inferred

GIS analysts · planners · hydrologists · geotechnical engineers

Limitations

Constraints llm-inferred

Data sources are Japanese (MLIT / 不動産情報ライブラリ); not applicable to the UK-focused catalogue scope · Requires a 不動産情報ライブラリ API application and API key before use · Local install needed: Python 3.10+ with git clone, venv and pip install; configured via Claude Desktop · OS support listed as Windows 10/11 or macOS 13+; Linux not listed · ENTRY tools field is empty, while DOCS name get_multi_api; parameter schema not documented · No update frequency, resolution, rate limits or per-dataset time spans documented · Documentation is in Japanese only

Useful for

Use cases llm-inferred

Reproject a site or survey raster to a UK projected CRS (e.g. EPSG:27700) with a recorded CRS justification before flood or drainage modelling · Clip and buffer vector site boundaries and study areas for a desk study or planning constraints check · Compute raster statistics on DEM or elevation tiles for catchment or drainage screening · Batch convert and simplify GIS layers into consistent formats for client handover

Audience llm-inferred

GIS analysts · flood consultants · drainage engineers · hydrologists · ecologists · planners

Limitations

Constraints docs-verified

Reflection middleware: tools whose methodology matters (e.g. raster_reproject, CRS choice, resampling) raise ToolError until a structured justification is supplied · Path access is restricted to GDAL_MCP_WORKSPACES; if unset, all paths are allowed and a warning is logged · Raster and vector tool sets are optional via RASTER and VECTOR environment flags · Input and output path parameters are not shown in DOCS; full parameters are in TOOLS.md, which was not supplied

Useful for

Use cases llm-inferred

Flood-zone constraint screening for a project area using fema_nfhl · Soil and farmland siting indicators for drainage or SuDS options using nrcs_soils · Species and critical-habitat screening for early ecological constraints using ipac · Composite constraints map of a project area for early site appraisal using map_composer

Audience llm-inferred

GIS analysts · flood consultants · ecologists · planners · civils and BIM engineers

Limitations

Constraints docs-verified

Screening and research aid only; does not make legal or agency determinations or replace agency or Tribal consultation · Does not guarantee that upstream datasets are complete or current · map_composer queries public GIS services at request time, so results depend on those services being available · census and epa_aqs return no data until their credentials are set

Example tool calls docs-verified

{
  "tool": "ipac",
  "arguments": {
    "roi": "<project-area geometry; parameter name not stated in DOCS>"
  }
}

Useful for

Use cases llm-inferred

Geofence alerts around a construction or remediation site perimeter for live TAK monitoring · Nearest field-team or asset lookup during a flood incident response · Distributing site survey or map data packages to field teams via TAK

Audience llm-inferred

emergency planners and incident responders using TAK · GIS analysts supporting live operations · civils site managers with TAK deployments

Limitations

Constraints llm-inferred

Requires a running TAK Server (TAK Server, FreeTAKServer or taky); no bundled data · Docs claim 11 tools but 13 are named in the metadata and the tool sections · Docs state test coverage is in progress and additional tool development is ongoing · Write actions (tak_send_cot_event, tak_send_emergency, data package upload) affect live TAK users · No UK grid (OSGB/BNG) support documented; examples use decimal-degree coordinates · Source repo mismatch: catalogue URL is github.com/jfuginay/tak-server-mcp, docs point to skyfi/tak-server-mcp and @skyfi/tak-server-mcp; verify provenance before installing · Env var names differ: docs use TAK_SERVER_CLIENT_CERT, catalogue lists TAK_SERVER_CLIENT_KEY only · Requires Node.js >= 18.0.0

Useful for

Use cases llm-inferred

Screening for active fires near a site using NASA FIRMS detections · Pre-event satellite imagery search and cloud-cover checks with Sentinel-2 or Landsat · Spectral index (NDVI/NDWI) calculation for vegetation or water-extent context · Terrain and elevation context for drainage or flood-risk desk studies

Audience llm-inferred

GIS analysts · environmental consultants · remote-sensing specialists · hydrologists

Limitations

Constraints llm-inferred

Not specific to UK water, drainage or civils; no UK-specific datasets identified in the docs · Docs excerpt is truncated before categories 9 to 27, so coverage of most tools is not verified · Planet Labs requires an API key · Sentinel-2 and Landsat download URLs require Copernicus or USGS authentication · Update frequency and output formats are not stated · Depends on third-party APIs whose rate limits and availability are not documented

Useful for

Use cases llm-inferred

NDVI or land-cover change over a site boundary for a BNG habitat baseline · Sentinel-2 cloud-filtered imagery review for a pre-development site condition survey · Zonal statistics of land use within a catchment as input to a flood risk or drainage desk study · Water-body extent change over time from Landsat for environmental permit or monitoring context

Audience llm-inferred

GIS analysts · ecologists · hydrologists · planners · environmental consultants

Limitations

Constraints docs-verified

Chrome Web Store version does not support local connections (MCP Server or Ollama); MCP requires the Developer Version from GitHub · Agent can only see code in temp/new scripts in the Google Earth Engine Code Editor, so scripts must be saved first · Z.AI models do not support screenshot analysis · Ask Mode is read-only and cannot insert, modify or execute code; Do Mode is required for execution

Useful for

Use cases llm-inferred

Flood risk screening using terrain-based flood modelling from satellite data · Vegetation index (NDVI) baseline for habitat context and change over a site · Water body monitoring time series for water quality change near a site

Audience llm-inferred

GIS analysts · hydrologists · flood consultants · ecologists · environmental consultants

Limitations

Constraints llm-inferred

Requires Google Earth Engine access and a service account key set via GOOGLE_APPLICATION_CREDENTIALS · Requires Node.js 18+, a local clone, npm build and server start before use · Setup is documented only for Claude Desktop on Windows (%APPDATA% config path) · Export formats are not documented; exports go to Google Drive, Cloud Storage or Earth Engine Assets · No temporal or spatial resolution or time span is stated; the global claim comes from entry metadata, not DOCS · UK-specific sources (e.g. EA gauges, OS data, UK DEM) are not documented; UK suitability needs testing · Flood, wildfire and water quality models are described only at feature-list level; no validation or accuracy is documented · DOCS reference ./docs/api.md, which was not provided, so tool parameters are undocumented

Useful for

Use cases llm-inferred

Flood extent screening for a site using Sentinel-1 SAR and JRC Global Surface Water history · Terrain and slope screening for drainage or civils options using SRTM 30m DEM · Vegetation (NDVI) and land cover baseline for BNG habitat screening using Sentinel-2 and Dynamic World

Audience llm-inferred

GIS analysts · environmental consultants · hydrologists · ecologists · drainage engineers · civils engineers · planners

Limitations

Constraints llm-inferred

Requires a Google Earth Engine account, a Google Cloud Project, and running earthengine authenticate · Runs locally via Python (pip install -e .) over stdio; not a hosted service · Built-in knowledge base lists global datasets only; no UK-specific sources (e.g. OS, EA LiDAR) are documented · Documentation is in Chinese · ENTRY auth is null although GEE authentication is needed · Maintenance status and update cadence are not documented

Useful for

Use cases llm-inferred

Flood risk context: GloFAS/EFAS river discharge series as catchment baseline inputs · Climate allowance inputs: ERA5 reanalysis extracts for drainage or flood risk climate-change baselines · Coastal studies: CMEMS wave and sea-level subsets as context for coastal flood or outfall design

Audience llm-inferred

hydrologists · flood risk consultants · drainage engineers · coastal engineers · GIS analysts

Limitations

Constraints docs-verified

Catalogue snapshots may lag the live Copernicus catalogues · CDS-family downloads depend on upstream queue availability; large requests may take minutes to hours · Size estimates are approximate and must not be used for quotas, billing or disk provisioning · Hierarchical routing is pattern-based; misroutes on ambiguous queries are possible · Requires Copernicus credentials and one-off dataset licence acceptance for some CDS datasets · Download location is fixed at server startup · CDSE, Sentinel Hub and WEkEO are planned but not yet supported · Requires Python 3.11+

Useful for

Use cases llm-inferred

Flood extent and onset from Sentinel-1 SAR after a storm event (sar_flood, sar_water) for flood risk assessment evidence · Upstream river flow context versus period mean at a site (river_discharge) for FRA baseline flows · Vegetation and water change detection across two dates at a site (eo_compare, eo_index) for pre- and post-works comparison · Long-run temperature and precipitation trend for a site (climate_history) for drainage design climate context

Audience llm-inferred

flood consultants · hydrologists · drainage engineers · GIS analysts · ecologists · planners

Limitations

Constraints llm-inferred

Not UK-specific: no UK gauge network or UK-specific dataset is listed in the docs · forest_alerts covers the tropics only · Copernicus, FIRMS and GFW tools need API keys or credentials · UNEP MARS methane data unavailable (no public API) · Project is new; the Earth Watch ledger feature is marked new (M1) · Many tools depend on third-party public APIs, so maintenance and availability risk is external

Useful for

Use cases llm-inferred

NDVI/SAVI vegetation-health screening of a site or catchment from Sentinel-2 for baseline ecology or land-use context · NDWI/MNDWI water-extent mapping of a UK reservoir, lake or floodplain for flood or drought context · NDBI built-up mapping and multi-date composites to track development change around a site · Random Forest land-cover classification with custom training points for habitat or land-use baselines

Audience llm-inferred

GIS analysts · ecologists · hydrologists · environmental consultants · planners · drainage engineers

Limitations

Constraints docs-verified

Hosted server runs on Render's free tier and may take 30 seconds to wake when idle · axion_sar2optical is only available through the hosted server · Exports over 10MB need S3, which requires AWS credentials and a bucket · NAIP imagery is US only · All data is accessed via the AWS Earth Search STAC API, a third-party dependency

Useful for

Use cases llm-inferred

Pre-survey screening of low-cloud Sentinel-2 scenes for a site AOI over a chosen date window · Terrain inputs from Copernicus DEM for catchment or drainage outfall assessment · Land-cover baseline from ESA WorldCover or IO LULC for habitat or planning context · Building footprint extraction from MS Buildings for flood exposure or drainage catchment screening

Audience llm-inferred

GIS analysts · hydrologists · drainage engineers · ecologists · planners

Limitations

Constraints llm-inferred

Supported datasets are listed in an external collections.md, which is not included in the provided docs · Place-name geocoding depends on the external Nominatim service · No UK-specific coverage or resolution details stated in the docs · Release history and maintenance status not stated in the docs

Useful for

Use cases llm-inferred

Debugging a Python or TypeScript drainage or hydraulic calculation script with agent-driven breakpoints and debug state inspection · Running GIS or model-processing scripts in a VS Code terminal and returning output to the agent · Refactoring data-processing code for a flood or BNG tool using get_references and rename_symbol to check blast radius · Catching type and lint errors in consultancy tooling with get_diagnostics before handover

Audience llm-inferred

software developers building consultancy tooling · GIS analysts scripting in VS Code · hydrologists and drainage engineers who code their own models

Limitations

Constraints llm-inferred

Local only: bound to 127.0.0.1, not reachable from other machines · No authentication: any other local process can run commands through the endpoint · Terminal execution and output buffering require VS Code shell integration; CMD is not supported natively · Not a data source: no geospatial, hydrological or environmental datasets, so the catalogue category 'gis' does not fit · Catalogue tool list omits terminal_run, which the docs list; pylon.* settings are listed as if they were tools · Version 0.5.0 is installed from a locally built .vsix, so maintenance and release cadence are unclear · Requires VS Code to be open with the extension running

Useful for

Use cases llm-inferred

Nearby asset and receptor queries from site coordinates (query_nearby, find_nearest) for constraints screening · Buffer and intersection tests on drainage or flood-risk layers (buffer_geometry, test_intersection, join_spatial) · Geometry QA on client GIS datasets before reporting (validate_geometries, table_info, spatial_extent) · Ad-hoc natural-language questions against a project PostGIS database (nl_to_sql)

Audience llm-inferred

GIS analysts · flood consultants · drainage engineers · hydrologists · planners

Limitations

Constraints llm-inferred

Tools only: no bundled datasets; you supply and maintain the PostGIS database · execute_sql requires user confirmation before running · Requires Python 3.8+ with psycopg2 and a PostGIS-enabled PostgreSQL database · Docs are in Chinese; no stated coverage, transport, rate limits, or maintenance status

Useful for

Use cases llm-inferred

FRA context: national river and lake layers for regional water-body mapping · Site context screening: boundary, transport and pipeline layers around a project site · Constraint screening: intersect pipeline or transport features with a study area using execute_sql · Desk-study GIS base layers for China-based projects

Audience llm-inferred

GIS analysts · planners · hydrologists (regional context only) · civils engineers (regional context only)

Limitations

Constraints llm-inferred

Data currency 2019 for the 2021 public edition · 1:1,000,000 scale is too coarse for site-level or detailed drainage/flood modelling · China-only coverage; CGCS2000 / SRID 4326, not British National Grid (EPSG:27700) · No UK datasets; cannot substitute for UK sources such as OS, EA or NRFA data · Requires local PostgreSQL/PostGIS setup, GDAL/OGR and manual GDB import via scripts before use · Data import is script-based, not an MCP tool; execute_sql allows SELECT only · Maintenance and support commitments are not stated in the docs

Useful for

Use cases llm-inferred

Digitise scanned geological or well-log figures into editable CorelDRAW files for report graphics · Re-vectorise low-quality JPEG site plans or flood-map images for client markup · Convert flowcharts or process diagrams from legacy reports into editable vector drawings

Audience llm-inferred

geotechnical engineers · hydrogeologists · GIS analysts · report graphics staff using CorelDRAW

Limitations

Constraints docs-verified

Windows only; CorelDRAW must be running; only CorelDRAW Graphics Suite 2022 (v24) verified · All Chinese text set in 新宋体; Latin serif vs sans-serif chosen per image and may be wrong · Labels left blank keep the original raster text as traced graphics, so manual cleanup may be needed · Text about 6-7 px high or smaller is unreliable and flagged for review · Region model covers colour-block diagrams only; small solid arrowheads and box borders are handled poorly · Self-check cannot detect loss of small solid elements such as arrowheads · Long jobs return status=running and need polling via cdr_job_status; CorelDRAW can slow or hang over long sessions · Delivery via cdr_finish is refused while issues remain unless accept_remaining is set · Consecutive spaces in titles are lost (OCR output has no spaces)

Useful for

Use cases llm-inferred

Pull levels, grids and rooms from an open Revit model to check a drainage or flood-risk layout against model geometry · Batch-update drainage or civils element parameters with setElementParametersBatch, then verify with modelHealth · Export schedules to Excel for quantity checks and re-import updated parameter values · Query element relationships (host, joined elements) before moving or deleting elements in a coordinated model

Audience llm-inferred

BIM and civils engineers · BIM coordinators · Revit automation developers · GIS and BIM analysts using MCP-enabled AI tools

Limitations

Constraints llm-inferred

Requires Windows 10/11 and a running Autodesk Revit session; the GraphQL server only runs after Start is pressed in the Add-Ins tab · Server port is auto-chosen from 5000–6000 and shown in a dialog; fixed-port clients must set REVIT_GRAPHQL_URL · Parameter values are passed as strings; typed storage handling is noted as extensible but not yet implemented · Angles are in radians and geometry is in Revit internal units (feet), so unit conversion is needed · Mutations such as deleteElements and moveElements write to the live model; undo behaviour is not documented · Entry describes the project as a weekend hackathon build, so maintenance and long-term support are uncertain · Entry licence is null and the entry URL (GraphBIM) differs from the docs clone URL (chuongmep); verify provenance before use · No MCP tool names are listed in the entry or docs, so MCP tool discovery is needed

Useful for

Use cases llm-inferred

Geocode site addresses to coordinates for a desk-based constraints screen · Locate watercourses, outfalls or pumping stations within a radius of a site for a drainage or FRA context map · Pull OSM features inside a local authority or catchment boundary for a planning or ecology baseline · Reverse geocode survey points to their nearest address for site records

Audience llm-inferred

GIS analysts · flood consultants · drainage engineers · ecologists · planners

Limitations

Constraints docs-verified

Nominatim is limited to one request per second; request starts are spaced 1,050 ms apart · Nominatim tools select objects by name, address, proximity or ID only, never by tag · Overpass tag filters take literal text; regex, alternation and negation require openstreetmap_query_raw · Overpass pages cap at 500 features and place search at 40 results per call · Overpass area data age is reported as areasTimestamp; a boundary ref that maps to no area returns an empty page · Data is ODbL-licensed and every response carries the ODbL attribution · Public Nominatim and Overpass endpoints are shared; heavy use needs a self-hosted or mirror instance · Server auth defaults to none (MCP_AUTH_MODE); OAuth is an optional server setting, not an upstream requirement

Useful for

Use cases llm-inferred

FRA baseline: watercourses and waterbodies within a site bounding box via get_waterways · BNG habitat baseline screening: green spaces (forest, meadow, grass, farmland) as desk-based land-cover context · Site context mapping: roads and railways for access and noise-source screening · Drainage strategy: building footprints in a catchment bounding box for a rough impermeable-area estimate

Audience llm-inferred

flood consultants · hydrologists · drainage engineers · ecologists · planners · GIS analysts

Limitations

Constraints docs-verified

DOCS recommend use only for education, research and non-profit purposes; commercial consultancy use needs checking against OSM and Overpass usage terms · Recommended bounding box 0.005° × 0.005° or smaller (about 500 m); maximum 0.001 square degrees to avoid timeouts; building queries are costlier than road queries · DOCS recommend no more than 1 request per second; results cached for 15 minutes (TTL) · Depends on public Overpass API servers with a 3-server fallback; availability not guaranteed · DOCS examples and performance figures are Tokyo-only; UK coverage and data quality not documented · Last changelog entry is v1.1.0 dated 2025-07-08; maintenance activity uncertain as of 2026-10 · ENTRY tools field lists input_path, output_path and query, which are parameter names, not tool names · OSM attribution and ODbL obligations not addressed in DOCS

Useful for

Use cases llm-inferred

Stormwater design rainfall inputs from NOAA Atlas 14 and IDF curves · Flood zone and wetland screening for US site due diligence · Water quality impairment screening using EPA ATTAINS 303(d) listings · Phase I ESA desktop data gathering from EPA sites

Audience llm-inferred

flood consultants · drainage engineers · hydrologists · ecologists · environmental consultants · civils engineers

Limitations

Constraints llm-inferred

US federal data only; no UK coverage, so not usable for UK-focused projects · Source count conflicts: entry metadata says 28+, DOCS say 80+ · Tool names are not listed in ENTRY or DOCS, so the tools array is empty · Requires Node.js v18+ and npx for the npm-installed server · Requires an emailed API key before first use · Burst rate limits are per-minute · A full site data collection takes roughly 60-120 seconds

Useful for

Use cases llm-inferred

US coastal flood-risk screening: CO-OPS water levels and flood statistics at a nearby tide station · Storm surge forecast comparison against tide-gauge observations for coastal flood assessment · Stream flow and NWS flood status checks near a US site via USGS Water Services · Wave and wind climate context from NDBC buoy observations for marine or coastal design

Audience llm-inferred

coastal engineers · hydrologists · oceanographers · GIS analysts · environmental consultants working on US projects

Limitations

Constraints llm-inferred

Coverage is US/NOAA-focused; no UK or European data sources are described · Several servers are not on PyPI and must be installed from source (vdatum-mcp, hpc-system-mcp, ufs-runner-mcp, alert-mcp) · hpc-system-mcp and ufs-runner-mcp require NOAA RDHPCS cluster access; ufs-runner-mcp submits real Slurm jobs · nos-workflow-mcp is experimental and not ready for general use · Data servers depend on upstream public NOAA, USGS and ERDDAP endpoints, so availability is outside the project's control · Monorepo has 13 published servers in the table, so each must be installed and configured separately

Useful for

Use cases llm-inferred

Re-running a shared capsule for a flood or drainage model after updated rainfall inputs · Releasing a versioned capsule or pipeline as a reproducible analysis record for a project deliverable · Managing data assets that hold survey or monitoring inputs for a civils or environmental study

Audience llm-inferred

hydrologists · drainage engineers · GIS analysts

Limitations

Constraints llm-inferred

Requires a Code Ocean platform account and access token · Tied to a specific Code Ocean deployment via CODEOCEAN_DOMAIN · Tested against a minimum Code Ocean platform API version; pin the package version to match the deployment · Local install needs uv and Python 3.10 or newer · Streamable HTTP refuses requests without a token · No environmental or UK geospatial datasets are described in the docs · No tool names are listed in the metadata or docs, so tool calls cannot be confirmed from this entry

Useful for

Use cases llm-inferred

Batch field additions and attribute calculations on drainage or site layers, driven from an AI chat prompt · Running GP tools (e.g. Buffer, Clip, Dissolve, Statistics) on flood-extent or catchment layers without manual geoprocessing dialogs · Exporting CAD/Excel outputs for civils or BIM handover, with outputs opened or added to the map automatically · Checking the open project and layer inventory before reporting on a planning or land-use GIS dataset

Audience llm-inferred

GIS analysts · civils/BIM engineers · drainage engineers · planners · hydrologists

Limitations

Constraints docs-verified

Windows 64-bit only; requires ArcGIS Pro 3.4+ · Requires ArcGIS Pro to be running · No authentication; service bound to 127.0.0.1 and must not be exposed to the local network · Destructive operations need explicit second confirmation from the user

Useful for

Use cases llm-inferred

Export a PNG of a live map view to check a flood-risk or drainage figure before issue · Read the current extent and selection in an open project to confirm a study area before geoprocessing · Apply undoable manual edits (move, merge, split, reshape) to drainage or habitat asset layers during digitising QA · Set and recall bookmarks and camera views so site-plan figures stay consistent across revisions

Audience llm-inferred

GIS analysts · ArcGIS Pro power users · flood consultants · drainage engineers · ecologists digitising habitat data

Limitations

Constraints llm-inferred

Requires ArcGIS Pro 3.x running with the add-in loaded; tools are unavailable when Pro is closed · Build requires Visual Studio 2022 17.13+ and the matching ArcGIS Pro SDK; not a pip-installable package · Server is localhost-only and tied to the Pro process · ModelContextProtocol packages pinned to 0.4.0-preview.3; bumping them breaks the build (maintenance risk) · Move, rotate and scale fail when selected features have different spatial references · Update or delete by object id silently no-ops if the id is stale · open_project does not open a view; a Pro restart returns to the Home screen with nothing open · Self-signed add-in shows as Untrusted in Pro's Add-In Manager on other machines · No execute_csharp escape hatch yet

Useful for

Use cases llm-inferred

Audit item sharing and group membership on an ArcGIS Online or Enterprise portal before handing a project folder to a client · Move or clone flood-model or survey Feature Layers between folders during a project handover · Query and edit drainage asset or consent-point Feature Layers from an AI agent with write mode enabled · Pull portal logs when a published water-level dashboard or service fails (Enterprise)

Audience llm-inferred

GIS analysts · GIS administrators · drainage engineers

Limitations

Constraints docs-verified

Webhooks, notebooks and federated servers are Enterprise-only; ArcGIS Server admin and portal logs are Enterprise features · Write operations are disabled by default and need ARCGIS_WRITE_ENABLED=true · GIS('Pro') mode needs ArcGIS Pro 3.3+; older Pro versions fall back to external Python and require .env auth · HTTP mode is for testing and development only, not production · Manages ArcGIS accounts and content rather than supplying UK environmental datasets

Example tool calls docs-verified

{
  "tool": "whoami",
  "arguments": {}
}

Useful for

Use cases llm-inferred

FRA baseline layer discovery and attribute queries against a council or Enterprise ArcGIS REST service · Geocoding site addresses and reverse-geocoding coordinates for a desk study · Pulling constraint layers from an ArcGIS service into a drainage or BNG screening review

Audience llm-inferred

GIS analysts · flood consultants · environmental consultants · planners

Limitations

Constraints docs-verified

Read-only: write operations (applyEdits, delete, publish) are out of scope for v1 · Queries capped at 5,000 records per request · Geocoding uses the AGOL World Geocoder unless ARCGIS_GEOCODER_URL is set · Portal search tools do not apply to standalone ArcGIS Server · Only stdio transport is available; streamable-http is on the roadmap · Write operations are roadmap only, behind a planned ESRI_MCP_ALLOW_WRITES gate

Useful for

Use cases llm-inferred

Load site boundary and raster layers from a prompt, then render map exports for report figures · Run QGIS processing steps (e.g. centroids) on consultancy vector layers and save outputs as GeoJSON · Generate thematic or choropleth maps from attribute fields for planning or FRA reports

Audience llm-inferred

GIS analysts · flood consultants · planners · hydrologists

Limitations

Constraints docs-verified

Only tested on QGIS 3.22 · Requires QGIS Desktop running with the plugin server started · execute_code runs arbitrary Python in QGIS and should be used with caution · Requires uv and Python 3.10 or newer · No licence stated

Useful for

Use cases llm-inferred

Flood exposure screening for a French study zone using the risque_inondation recipe · Building density and land-cover baseline for a site in France · Coastal land-pressure analysis from DVF transactions for a French coastal scheme · Print-ready PDF maps and QField data-collection packages for site visits in France

Audience llm-inferred

GIS analysts · flood consultants · planners · hydrologists · civils engineers

Limitations

Constraints docs-verified

Catalogue is France-only (IGN and French national datasets); no UK data sources documented · Production-ready only for single-user local deployments; multi-user mode is beta · Requires Docker and a running QGIS Desktop instance · Default WORKSPACE_AUTH_MODE is permissive: unauthenticated non-loopback calls are served · ign_dem_altitudes is compute-only and not renderable · Jobs over 30 s should use async tools; restart_qgis_engine causes 5-15 s of unavailability · Developed at Cerema Méditerranée; long-term maintenance not documented

Useful for

Use cases llm-inferred

Scripting QGIS project setup from prompts: create project, load boundary and DEM layers, zoom to AOI · Running centroid or other processing algorithms on catchment or parcel layers with saved outputs · Generating choropleth or constraint map renders for planning and FRA figures · Prototyping PyQGIS analysis scripts before moving them into a production workflow

Audience llm-inferred

GIS analysts · flood consultants · hydrologists · planners · drainage engineers

Limitations

Constraints llm-inferred

Only tested on QGIS 3.22 and 3.34 · QGIS desktop must be open with the plugin server started manually · execute_code runs arbitrary Python and the docs advise caution · Community fork of jjsantos01/qgis_mcp; maintenance risk · No authentication documented

Useful for

Use cases llm-inferred

Clip and reproject site boundary and constraint layers via execute_processing before a planning submission · Render a constraints or flood-extent map to PNG with render_map_base64 for a report figure · Export cleaned survey or asset layers to GPKG with export_layer for a client GIS deliverable

Audience llm-inferred

GIS analysts · flood risk consultants · ecologists · planners

Limitations

Constraints docs-verified

Upstream only tested on QGIS 3.22; this fork verified against QGIS 4.2.0 only · Requires QGIS to be open with the server started · execute_code is opt-in and powerful; use with caution · Docs describe a modified v3.0.0 fork of upstream jjsantos01/qgis_mcp, so version and maintenance drift risk · Entry lists 22 tools; docs describe 46 commands · Licence not stated

Useful for

Use cases llm-inferred

Prompt-driven loading and styling of site or catchment layers into a QGIS project · Running Processing algorithms such as centroids on consultancy vector data · Rendering map figures for FRA or planning report appendices · Scripted PyQGIS attribute checks on shapefile or GeoPackage datasets

Audience llm-inferred

GIS analysts · flood consultants · drainage engineers · hydrologists · planners

Limitations

Constraints llm-inferred

Requires QGIS running locally with the plugin socket server started manually · Docs state QGIS 3.X but only tested on 3.22 · execute_code runs arbitrary Python and needs caution · DOCS describe jjsantos01/qgis_mcp, but ENTRY URL is the kicker315 fork, so behaviour may differ · No data coverage: this is a tool, not a dataset · Tool parameter schemas are not given in DOCS

Useful for

Use cases llm-inferred

Buffer drainage outfalls or watercourse setback zones for a site boundary or constraints layer · Overlay flood-zone or habitat polygons with a development site to screen constraints · Run GDAL raster or vector preprocessing on GIS inputs before hydrology or drainage modelling

Audience llm-inferred

GIS analysts · civils engineers · drainage engineers · environmental consultants · developers building LLM-driven QGIS agents

Limitations

Constraints llm-inferred

Requires QGIS 3.22+ with Python bindings installed locally · Requires Python 3.10-3.11 · All 14 services must be started locally (ports 32821-32834) before the agent can connect · Natural-language task handling depends on an external OpenAI or compatible LLM API · README contains placeholder repository links, so maintenance status is unclear

Example tool calls docs-verified

{
  "tool": "buffer",
  "arguments": {
    "INPUT": "/path/to/input.shp",
    "DISTANCE": 500,
    "OUTPUT": "/path/to/output.shp"
  }
}

Useful for

Use cases llm-inferred

Pre-flight CRS, extent and null-geometry checks on client layers in QGIS before a flood or drainage model build · Render the current QGIS map view to an image for a site-context figure in a report · Run QGIS Processing algorithms (e.g. clipping catchment layers) from a Codex session

Audience llm-inferred

GIS analysts · flood consultants · drainage engineers · hydrologists

Limitations

Constraints llm-inferred

execute_code runs arbitrary PyQGIS inside QGIS Desktop and should be used sparingly · QGIS Desktop must be open with the plugin server running on port 9877 · Setup is documented for Windows (PowerShell packaging helper, Windows paths) · Port conflicts need manual edits to the plugin UI and the bundled server default · Derived from the Claude-oriented jjsantos01/qgis_mcp project; no licence stated

Useful for

Use cases llm-inferred

Editable QGIS map and print layout of site or gauge points from a client spreadsheet for a flood or drainage report · Interpolated surface or contour map from point survey readings for a ground-conditions or drainage strategy appraisal · Getis-Ord Gi* hotspot or KDE map of asset or incident locations for a planning or environmental baseline · Bivariate or graduated choropleth atlas of catchment or area-based statistics for a client deliverable

Audience llm-inferred

GIS analysts · flood consultants · drainage engineers · hydrologists · ecologists · planners

Limitations

Constraints docs-verified

Requires QGIS desktop open with the QGIS MCP plugin server started (port 9876) · SKILL.md and most references are in Chinese; algorithm-reference.md is English · Without an MCP connection only a static preview sketch is possible, not a QGIS deliverable · Ships synthetic example data only; real field data must be kept out of public forks · Not a data source: the user must supply the tabular or spatial data

Useful for

Use cases llm-inferred

Web map viewer of flood-zone and site-boundary layers in a Mapbox GL JS app, driven by an AI agent · Drawing proposed drainage routes or SuDS locations as GeoJSON over 3D terrain for client presentations · Flying the map camera to catchment or site extents for stakeholder consultation maps

Audience llm-inferred

GIS analysts · planners · civils and drainage engineers building web map viewers

Limitations

Constraints llm-inferred

Map control only: no datasets (rainfall, river levels, DEM, flood extents) are offered · Needs a Mapbox GL JS map open in a browser with the bridge connected to ws://localhost:9200 · Only 5 default toolsets (about 30 tools) are active; draw, style and 3d must be enabled with enable_toolset · ENTRY lists only list_toolsets and enable_toolset, while DOCS describe 40+ tools · ENTRY auth cites env var YOUR_TOKEN, but DOCS show the token entered on the browser page

Example tool calls docs-verified

{
  "tool": "flyTo",
  "arguments": {
    "center": [
      2.2945,
      48.8584
    ],
    "zoom": 16
  }
}

Useful for

Use cases llm-inferred

Preliminary hazard screening (earthquakes, volcano alert level, typhoons) for a Philippine overseas project site · River flood outlook for a Philippine city or catchment via get_flood_forecast · Procurement and infrastructure-spending review for a Philippine client bid using PhilGEPS notices · Population and poverty baseline for a Philippine development project area

Audience llm-inferred

hazard and risk consultants · GIS analysts · international development consultants · planners

Limitations

Constraints llm-inferred

Philippines-only data, so not relevant to UK sites; the ENTRY regions field wrongly says United States · Catalogue auth field lists PAGASA_API_TOKEN, which conflicts with the docs' no-API-key statement; verify before use · Many sources are scraped HTML, PXWeb JSON or undocumented APIs, so upstream changes can break tools · Election tools read an archive frozen on 2025-05-16 · query_psa_dataset needs an explicit code for every dimension, refuses 'all' and '*', caps at 1000 cells, and needs describe_psa_dataset first · Upstream outages return upstream_error envelopes, not empty lists; handle that flag explicitly · Heuristic indicators are statistical only; allegations need independent investigation and a second source · Each HDX dataset has its own licence; check license_id before reuse · ENTRY tools field lists status values (success, empty, etc.), not tool names; see docs/tool-reference.md

Useful for

Use cases llm-inferred

Testing design-storm depth scenarios on an existing SWMM drainage model · Identifying nodes that flood under a given storm for a drainage strategy review · Assessing detention storage placed at a node to reduce downstream flooding · Comparing base and modified outfall hydrographs for a drainage design option

Audience llm-inferred

drainage engineers · hydrologists · flood consultants · civils engineers

Limitations

Constraints llm-inferred

Requires a local install (uv, cloned repository) and client configuration; not a hosted service · change_storm only sets a 24-hour SCS Type 2 design storm of a given depth · change_conduit only changes the diameter of circular conduits · add_storage replaces a junction with a cylindrical storage node · Tool argument schemas are not documented in DOCS · Claude Desktop on macOS may need a uv symlink to be found · No area or time-span coverage stated; depends on the SWMM models the user supplies

Useful for

Use cases llm-inferred

Locate French river flow or hydrometric datasets for a cross-border comparison or desk study · Find French water-quality or flood-related open datasets for a transboundary catchment review · Identify French geocoding dataservices (e.g. Adresse API) to place French site addresses

Audience llm-inferred

GIS analysts · hydrologists · environmental consultants · planners

Limitations

Constraints llm-inferred

Covers French open data from data.gouv.fr only; no UK datasets · Streamable HTTP transport only; STDIO and SSE are not supported · Public hosted endpoint: no availability guarantee stated in docs · Results depend on the metadata and quality of third-party datasets on data.gouv.fr · Documented parameters are given only for search_datasets; other tools are not described in detail

Useful for

Use cases llm-inferred

Desk-study search of a CKAN portal for open environmental or flood-related datasets to scope a site baseline · Checking whether a local authority's CKAN portal publishes drainage or asset datasets before making a data request · Pulling DataStore tabular monitoring records via SQL into a spreadsheet for trend analysis · Reviewing dataset resource formats and metadata to confirm reuse suitability for a client report

Audience llm-inferred

GIS analysts · hydrologists · environmental consultants · drainage engineers · planners

Limitations

Constraints docs-verified

Tool output capped at 50,000 characters; oversized text and Markdown responses are cut · ckan_datastore_search returns 100 rows by default, maximum 32,000 · ckan_package_search returns 10 results per page by default, maximum 1,000 · Hosted endpoint shares a 100k requests/day quota · HTTP response body capped at 32 MiB (CKAN_MAX_RESPONSE_BYTES for local Node.js deployments) · ckan_find_portals relies on the datashades.info live registry (~950 portals)

Useful for

Use cases llm-inferred

Building footprint extraction from aerial imagery as exposure or drainage catchment inputs · Water-body segmentation from satellite or aerial imagery for flood extent baseline mapping · Bi-temporal change detection for land-use or built-form change screening across survey dates · GFM embedding similarity and clustering to zone a site or study area by surface form

Audience llm-inferred

GIS analysts · remote sensing analysts · flood consultants · hydrologists · ecologists · planners

Limitations

Constraints docs-verified

Embedding tools (tessera, gse, galileo) need a proxy to reach Google-hosted data; without one they return a structured error rather than results · GEE-backed embeddings require Google OAuth, non-commercial registration and project binding · On-the-fly embeddings for other models (e.g. prithvi) are an unchecked roadmap item · finetune_remote (TerraTorch via Colab) is roadmap only and is not among the 16 tools · Verified only on Windows 11 x64, CPU-only; other platforms and GPU use are not documented · Upstream geoai 0.42.0 masks_to_vector regularize bug is worked around by fixing regularize=False · Heavy tests need a sample imagery file, and model weights download on first use · Pre-1.0 version (0.2.x) with heavy upstream dependencies (geoai-py, torch, rs-embed)

Useful for

Use cases llm-inferred

Baseline vs upgraded drainage network scenario runs with mike_run and mike_results_compare · Flood-node screening by ranking peak water level against ground level from a MIKE+ run · Converting design-storm rainfall CSVs to MIKE+ .dfs0 inputs · Importing SWMM/EPANET models into MIKE+ and writing provenance manifests for QA

Audience llm-inferred

drainage engineers · flood consultants · hydrologists

Limitations

Constraints docs-verified

Experimental / pre-release status · Run, edit and import need a licensed MIKE+ 2026 install and Windows with Python 3.11 x64 · Verified end to end only on the MIKE+ 2026 Sirius_RTC example · mikeplus requires Python 3.9-3.11, so Python 3.12+ is not supported

Useful for

Use cases llm-inferred

Review a river-crossing flood impact assessment chapter against initial design and construction drawings, listing data conflicts, assumptions and open items · Set up P-III frequency analysis and design flood checks for a channel or river-crossing project, with a data-gap table before calculation · Check open-channel water surface profile, weir and hydraulic jump assumptions as a second-pass review of a drainage or hydraulic calculation · Structure a feasibility or preliminary design report by checking data closure and calculation linkage across chapters

Audience llm-inferred

hydrologists · hydraulic engineers · flood risk and flood impact assessment consultants · dam, sluice and levee structural engineers · report reviewers

Limitations

Constraints llm-inferred

Public version excludes personal, project and classified material, so no project data is included · Built around Chinese engineering practice and Chinese standards; not directly applicable to UK standards without adaptation · Software tools such as HEC-RAS and MIKE 11 are referenced only; the skill does not run models · Numerical inputs must be verified against authoritative design data and current codes; missing data is flagged as to be confirmed rather than filled in · Young project with two releases (v1.0.0 in June 2026, v1.0.1 in July 2026), so maintenance history is short

Useful for

Use cases llm-inferred

Publish a git-backed, rollback-able Portolan catalog for flood or drainage datasets using git-backed-catalog · Convert a council ArcGIS/WFS service or folder of shapefiles into a documented Portolan catalog using portolan-bootstrap · Query GeoParquet and COG data with DuckDB for site-scale analysis using reading-portolan · Generate checked thumbnails for catalog collections using portolan-thumbnails

Audience llm-inferred

GIS analysts · geospatial data engineers · environmental data managers

Limitations

Constraints llm-inferred

Instructional skill files only; no datasets are bundled · Skills track pinned versions of portolan-cli, rashid, the spec and the catalog template, so they may drift from newer releases · portolan-thumbnails requires Node.js 24.12 or newer · Requires a Claude Code, Gemini CLI, Codex CLI or other SKILL.md-compatible agent to use

Useful for

Use cases llm-inferred

Literature review to support a flood-risk or drainage design assumption using /lit-review · Publication-style audit of model or monitoring charts before they go into a client report using /figure-review · Stress-testing a flood or water-quality modelling claim for baseline and uncertainty using /reviewer-2 · Senior-engineer review of an in-house analysis repo before handover using /ai-review

Audience llm-inferred

Researchers using Claude Code for scientific computing · Climate and atmospheric scientists · Scientific software developers · Analysts building AI-assisted analysis workflows

Limitations

Constraints docs-verified

Developed on macOS and Linux; on Windows the shell layer does not run, so skills with shell preambles (handoff, pickup, figure-review, repo-init) fail · Session auto-naming hook works only with iTerm2 or VS Code · Zotero write, Notion work journal and session-name generation need extra configuration · No datasets, gauge feeds or data APIs are described; the toolkit offers skills, reviewer agents and shell utilities only · No UK water, civils or environmental content is described

Useful for

Use cases llm-inferred

Seasonal forecast baseline series from 1993 to present for drainage or flood-risk climate context (monthly_mean with a computed ensemble mean) · ERA5 historical rainfall and temperature inputs for a catchment or drainage assessment background · Climate context download for water resource or civils design discussions

Audience llm-inferred

hydrologists · flood consultants · drainage engineers · climate or data analysts

Limitations

Constraints docs-verified

Early stage: only the cds-download skill is available; more skills are planned · The ensemble_mean product type only covers real-time years (~2017 onward); 1993-present requires monthly_mean and a manually computed ensemble mean · No GHCN station parsing or QC-flag skill yet (planned)

Useful for

Use cases llm-inferred

Site-visit weather log for UK or non-US sites using wx_conditions or wx_global, as an audit record of conditions · Derived atmospheric parameters (dewpoint, CAPE, LCL) via wx_calc for technical notes or drainage and flood input checks · Forecast briefing for construction or monitoring work windows using wx_brief or wx_forecast · NWP field and radar figures for client report appendices using wx_model_image or wx_radar_image

Audience llm-inferred

hydrologists · drainage engineers · environmental consultants · GIS analysts

Limitations

Constraints docs-verified

Native data sources are US-focused (NWS, SPC, NEXRAD); non-US coverage relies on Open-Meteo via wx_global · No UK-specific source (e.g. Met Office) is listed · Image and calculation tools require optional Rust packages; radar needs a source build and RADAR_RENDER_PATH · Built for Claude Code; configuration is via ~/.claude/settings.json and needs a restart · Rate limits and upstream availability are not documented · Community project; maintenance commitment is not documented

Useful for

Use cases llm-inferred

Tide and surge-context review for coastal flood risk assessment at US comparison sites · Sea level trend and 2022 SLR projection inputs for coastal climate-resilience appraisal (US sites) · Tidal datum (MLLW, MSL, NAVD88) and harmonic constituent checks for estuary or outfall modelling (US stations) · Marine wind and wave briefing for coastal works programme planning (US waters)

Audience llm-inferred

flood consultants · coastal engineers · hydrologists · marine civils engineers · planners

Limitations

Constraints llm-inferred

Great Lakes stations have no tide predictions · Subordinate (S) prediction stations only support hilo predictions · Predictions are astronomical; storm surge is not included · Per-product request-span limits are enforced client-side (e.g. 4 days for 1-minute data) · Oversized results return a response_too_large error rather than truncated data · NWS forecasts are limited to US lat/lon, up to about 7 days · No UK station coverage is stated; the NOAA network is US-centred · Tool argument names are not documented in DOCS; verify against the tool schema

Useful for

Use cases llm-inferred

Convert site addresses or town names to lat/long to feed FRA or gauge-proximity lookups · Geocode project sites for planning or environmental data queries that need coordinates · Supply coordinates to downstream GIS or API tools for drainage or flood-risk screening

Audience llm-inferred

GIS analysts · hydrologists · flood consultants · drainage engineers · planners

Limitations

Constraints llm-inferred

Single tool only (mcp_geocoding_get_coordinates); no reverse geocoding documented · Result count capped at 10 per query · Depends on the public Nominatim service; upstream availability and usage policy are not stated in the docs · Described as a basic server; ambiguous UK place names may need more specific queries · Requires Python 3.12+ and uvx or pip to install (per docs tooling)

Useful for

Use cases llm-inferred

Geocode site addresses to coordinates for flood risk or drainage site location plans · Sample elevations at site points for preliminary civils levels checks · Compute drive-time matrices between project sites and suppliers for site logistics · Find nearest roads to a site for access route appraisal

Audience llm-inferred

GIS analysts · civils engineers · drainage engineers · planners · flood consultants

Limitations

Constraints llm-inferred

Requires a Google Maps Platform API key and billing enabled · Each tool needs its specific Google Cloud API enabled (Places API (New), Routes API, etc.) · Default rate limit of 100 requests per minute per endpoint unless configured · IP override is best-effort and private/reserved IP ranges are rejected · UK-specific coverage and data currency are not stated in the docs · Third-party community project; maintenance risk not assessed

Useful for

Use cases llm-inferred

Index shared-drive shapefiles and PostGIS tables for a flood-risk or drainage project data room, searchable by metadata · Publish a shared map of survey or site-investigation layers as a link or embed for client review · Serve catalogued vector layers to QGIS or ArcGIS via OGC API Features for FRA or environmental baseline work · Run buffer, clip, and intersect analysis on consultancy layers, such as constraint buffers around watercourses

Audience llm-inferred

GIS analysts · flood consultants · drainage engineers · ecologists · planners

Limitations

Constraints docs-verified

Read-only MCP server for coding agents (per docs) · Self-hosted: requires a running GeoLens stack of six containers (about 1.3 GB resident) · WFS, ArcGIS, and OGC API Features imports are one-shot copies, not live · Map previews capped at 500 features; dissolve is materialize-only · GeoLens's own REST API can change between minor releases; standards APIs track their specifications · Semantic search needs an embedding provider and admin setup · No MCP tool names are given in the metadata or docs

Useful for

Use cases llm-inferred

Flood exposure screening for a French site: run risque_inondation to get flood zones and building exposure · Field survey prep: export a QField-ready ZIP with an editable Observations layer for site visits · Land-cover and hydrography baseline for a study area using set_study_zone and smart_load

Audience llm-inferred

flood consultants · GIS analysts · planners · environmental consultants · hydrologists

Limitations

Constraints docs-verified

Production-ready only for single-user local deployments; multi-user mode is beta · Requires a Docker host (docker compose) · Datasets are French national sources (IGN, DVF); no UK-specific data is documented, so UK use is limited · ign_dem_altitudes is compute-only and not renderable · restart_qgis_engine causes 5-15 s of unavailability · Jobs expected to exceed 30 s should use async tools to avoid timeouts · skill://file-exchange (bridge_put/bridge_get) is pending implementation · Default WORKSPACE_AUTH_MODE is permissive: unauthenticated non-loopback calls are served

Useful for

Use cases llm-inferred

Converting site addresses from a client or planning list into coordinates for FRA or drainage site location plans · Batch geocoding an asset, gauge or monitoring-point register supplied as addresses · Reverse geocoding survey or GIS coordinates into readable addresses for reports · Screening distances between a development site and nearby receptors or gauges, using coordinate pairs

Audience llm-inferred

GIS analysts · flood consultants · drainage engineers · civils engineers · planners

Limitations

Constraints docs-verified

Geocode and reverse-geocode tools return None if the location is not found or an error occurs, rather than raising an error · Geocoding calls are rate-limited to avoid exceeding provider quotas, so batch jobs run slowly · Distance tools return None if either address could not be geocoded · Default provider is Nominatim; switching to ArcGIS or Bing needs environment variables, and extra options need edits to geo.py · Requires Python 3.6+ and the fastmcp and geopy packages

Useful for

Use cases llm-inferred

Preview and compare candidate basemap styles for a client web map or flood-risk viewer · Quick visual check of site boundary or drainage-asset GeoJSON via geojson.io before sharing with a client · Audit which Mapbox token scopes a GIS web map deployment actually needs

Audience llm-inferred

GIS analysts · web mapping developers · drainage engineers reviewing GeoJSON outputs

Limitations

Constraints llm-inferred

GeoJSON preview tool is Beta · Each tool needs a token with specific scopes; wrong scope causes authentication errors · Preview style tool needs at least one public token with styles:read scope · Developer and styling tooling only; provides no environmental or hydrological datasets · Hosted endpoint is a separate devkit URL; the linked hosted-MCP guide points at a different endpoint

Useful for

Use cases llm-inferred

FRA baseline flows from nearest gauge using gdf-statistics (mean flow, Q95, Q50) · QMED and peak-flow statistics for flood estimation cross-checks · Catchment descriptor extraction (land cover, geology, FEH descriptors, SAAR) for hydrological inputs

Audience llm-inferred

flood consultants · hydrologists · drainage engineers · GIS analysts

Limitations

Constraints docs-verified

Test service: URL patterns, parameters and data formats may change before an operational release · No access controls currently, but this may not always be the case · Time-series requests accept only a single station and a single data-type per call · Update schedule is referenced on the NRFA site but not stated in the docs

Useful for

Use cases llm-inferred

Scottish FRA baseline flows and levels from the nearest SEPA gauging station · Calibrating or validating Scottish hydrological and hydraulic models against observed river levels · Low-flow and dry-weather baseline for water environment or abstraction assessments in Scotland

Audience llm-inferred

flood consultants · hydrologists · drainage engineers · GIS analysts

Limitations

Constraints docs-verified

Access keys are complicated to use, so the docs recommend accessing data without a key where possible · The documentation site is marked BETA

Useful for

Use cases llm-inferred

Drive a 3D terrain or site view of a proposed drainage or channel scheme from natural-language prompts during client meetings · Load survey or flood-extent GeoJSON into a browser Cesium viewer to review extents and feature values · Build an in-house browser assistant that lets engineers query and control a 3D project map

Audience llm-inferred

GIS analysts · civils engineers · flood consultants · web developers building map-based AI assistants

Limitations

Constraints docs-verified

Demonstration scenes use demonstration data, not surveyed heights or official statistics · WebMCP browser path is Chrome 149+ experimental · Codex map plugin is a community beta and requires a compatible MCP Apps host

Example tool calls docs-verified

{
  "tool": "openCesiumMap",
  "arguments": {}
}

Useful for

Use cases llm-inferred

Pre-scope satellite imagery availability (Ready vs Archived) over a site before committing to a download · Find dated scenes over a catchment for flood event or land-cover baseline review · Save recurring study-area searches for reuse in monitoring or EIA baseline work

Audience llm-inferred

GIS analysts · flood consultants · ecologists · planners

Limitations

Constraints llm-inferred

Downloads and cart require a Bhoonidhi login (bhd auth login or env vars) · Archived scenes may need a request on the portal before they can be downloaded · Priced and on-order scenes are only staged to the cart; ordering and payment happen on the Bhoonidhi portal · Background download jobs last only as long as the server process; large downloads should use the standalone bhd CLI · Imagery is under the Bhoonidhi EULA: credit ISRO-IRS and do not resell original products commercially · Archive time span and per-mission resolution are not stated in DOCS · Third-party community project; maintenance commitment not stated

Useful for

Use cases llm-inferred

Provision PostGIS or GeoPackage datastores and publish vector layers to GeoServer for project map services · Upload and assign SLD styles to flood, drainage or habitat layers via the MCP tools · Configure and seed GWC tile caches for client-facing basemaps

Audience llm-inferred

GIS analysts · GIS developers · GeoServer administrators

Limitations

Constraints llm-inferred

Management service only: configures GeoServer but provides no geospatial data of its own · Requires a reachable, running GeoServer instance with admin credentials · Local install from source; no hosted version described in docs · Licence not stated in docs or entry · Entry auth says 'API key', but docs specify GeoServer admin username and password · Entry tools field lists 'config.py' (a source file); exact MCP tool names are not given in docs · MCP transport (stdio or HTTP) not stated · Documentation is in Turkish

Useful for

Use cases llm-inferred

Geocode site addresses to coordinates for FRA or drainage site-location plans · Estimate drive or walk distances and durations from a site to suppliers, depots or monitoring points · Build a distance matrix to plan site visit or survey routes across several locations · Find nearby schools, hospitals or other sensitive receptors within a radius for screening

Audience llm-inferred

GIS analysts · planners · civils engineers · site investigation teams · environmental consultants

Limitations

Constraints docs-verified

Public Nominatim, OSRM and Overpass servers are shared open endpoints: use them lightly and fairly · Production use is recommended on self-hosted Nominatim and OSRM servers (set via env vars) · Requires Node 20+

Example tool calls docs-verified

{
  "tool": "geocode",
  "arguments": {
    "address": "New York",
    "limit": 1,
    "countrycodes": "us"
  }
}

Useful for

Use cases llm-inferred

Flood-extent and river surface visualisation for FRA or flood-event briefings in a WebGIS dashboard (water surface effect) · Pressure-flow animation on water network pipes for options presentations to clients (pipe flow effect) · Radar or scan-cone overlays on a digital twin of a site for client-facing 3D dashboards

Audience llm-inferred

GIS analysts · web and front-end developers building WebGIS dashboards · digital twin and BIM/3D visualisation teams

Limitations

Constraints docs-verified

Visualisation effects only; it supplies no hydrological, rainfall, gauge or survey datasets · Host project must provide its own Cesium version, static assets, CESIUM_BASE_URL and Viewer initialisation · Public demo is not live until GitHub Pages is enabled · Docs state no coverage, resolution or update cadence for any data · No MCP tool names are documented, so MCP tool use cannot be verified from the docs

Useful for

Use cases llm-inferred

Site context imagery: clip configured imagery to a site boundary and export GeoTIFF for report figures · Site history review using Esri Wayback historical imagery versions · Catchment screening: DEM GeoTIFF extraction for drainage and flood baseline checks · Boundary prep: convert KML/SHP/GeoPackage site boundaries and clip OSM vector layers

Audience llm-inferred

GIS analysts · flood consultants · drainage engineers · planners · environmental consultants

Limitations

Constraints docs-verified

Windows x64 desktop app only · Version 0.2.x; earlier builds are public test releases · Connecting to a data source does not grant download rights; licensing must be checked per provider · No UK-specific sources documented; examples are China-focused (e.g. Tianditu needs own credentials) · Historical imagery release date is not the capture date · Scanned PDF auto page-splitting still pending; OCR removed from base package · Trial credits limited to first 100 eligible accounts · Scheduled tasks require the local app to keep running in the background

Useful for

Use cases llm-inferred

Literature review and ranked research-gap analysis for a drainage or flood-risk evidence base before writing a technical note · Novelty check and spatial regression (OLS/GWR) on catchment attributes to support an evidence-based method statement · Dataset discovery and download with provenance logging from government portals for baseline environmental data · Consolidating pipeline outputs into a narrative technical report

Audience llm-inferred

GIS analysts · GIScientists · remote sensing researchers · geoscientists

Limitations

Constraints llm-inferred

Built for academic research workflows (papers, journal templates, reviewer loops); consultancy deliverables such as FRA or drainage design are not covered by the docs · Delivered as Claude Code skills (Markdown workflows), not as a standalone MCP data server; the tool names listed are skills · Requires Claude Code and paid Anthropic API usage · Track B spatial work needs a conda environment with geopandas, pysal, libpysal, esda, spreg, mgwr, rasterio and xarray; Track A deep-learning work needs a CUDA GPU (optional) · Requires copying the skills folder into ~/.claude/skills or a project .claude/skills directory before use · Licence not stated in metadata; maintenance status unknown · Automated pipelines are intended to run with human checkpoints; output needs expert review

Example tool calls docs-verified

{
  "tool": "lit-review",
  "arguments": {
    "$ARGUMENTS": "SuDS performance evidence for UK urban drainage strategies"
  }
}

{
  "tool": "data-download",
  "arguments": {
    "$ARGUMENTS": "UK river gauge daily flow records for the Thames catchment"
  }
}

{
  "tool": "spatial-analysis",
  "arguments": {
    "$ARGUMENTS": "Test whether catchment rainfall-runoff relationships vary spatially, with ESDA and conditional diagnostics"
  }
}

Useful for

Use cases llm-inferred

Buffer watercourses, clip a DEM to the buffer and derive slope for a site or FRA-style terrain screen (mirrors the documented quickstart example) · Select drainage or utility assets by attribute or geometry to map site constraints · Save a verified processing chain as a .model3 and re-run it on other catchments or sites

Audience llm-inferred

GIS analysts · Flood consultants · Hydrologists · Drainage engineers · Civils engineers working in QGIS

Limitations

Constraints llm-inferred

Requires a desktop QGIS installation; it is a QGIS plugin, not a standalone server or MCP endpoint · Dependencies must be installed from the Settings tab (Check / Install Dependencies) before use · OpenAI, Gemini and Anthropic need API keys, which conflicts with the ENTRY note that no credentials are documented · Output quality depends on the chosen LLM and on the data QGIS can load; no data coverage or resolution is defined by the plugin · Combined work is governed by QGIS GPL v2+ and PyQt GPL v3 terms alongside the MIT licence · No version, release status or maintenance information is given in the docs

Useful for

Use cases llm-inferred

Buffer and overlay of watercourse and flood-zone layers against a site boundary for FRA screening · Raster preprocessing of satellite imagery for before/after burn-scar or land-cover change mapping · Layer styling and map layout of constraint layers for planning or BNG habitat report figures

Audience docs-verified

GIS analysts · researchers · remote sensing practitioners · organisations and institutions

Limitations

Constraints llm-inferred

Early beta: participation by enquiry; the docs give a 2026 Q2 official launch target (by 30 June 2026) that has passed, and current release status is not stated · Requires QGIS desktop with the plugin installed (inferred from plugin type) · Underlying LLM provider, API key and cost requirements are not documented · No documented data coverage, formats, resolution, update frequency or rate limits; it is a workflow tool, not a data source · Licence not stated

Useful for

Use cases llm-inferred

Buffer site boundaries and overlay with flood-zone or constraint layers via execute_processing · Reproject and clip client GIS layers to a common CRS for drainage or planning baselines · Batch-export per-feature map sheets and attribute tables to CSV for planning reports

Audience llm-inferred

GIS analysts · flood consultants · drainage engineers · planners

Limitations

Constraints docs-verified

Requires the QGIS 3.22+ desktop application · execute_pyqgis runs inside the QGIS process with AST scan, whitelist and confirmation, not a full sandbox · User skills run in-process with the current user's permissions · LLM features need a configured OpenAI-compatible endpoint and network access · Optional MCP export is off by default, listens on 127.0.0.1 and requires a token · Docs mix current features with historical roadmap notes; feature status follows code wiring · Ships no bundled UK or environmental datasets; works on user-supplied layers · ENTRY tools list includes skills (web_search, gis_data_search, format_results, run via run_skill) and a data file (tool_docs_index.json), not callable tools

Useful for

Use cases llm-inferred

Identify unknown shapefile or GeoPackage layers received from clients or open-data portals (fields, feature count, sample rows) before planning analysis · Check raster extent, pixel size and band statistics for DEM or GeoTIFF inputs before flood or drainage modelling · Draft plain-language dataset descriptions for project data registers or handover notes

Audience llm-inferred

GIS analysts · hydrologists · ecologists · planners

Limitations

Constraints docs-verified

Requires Ollama installed and running locally with at least one model; no hosted option is described · Vector input limited to .shp and .gpkg; raster input limited to .tif, .tiff and .img · Attribute context limited to a sample of 10 rows · Responses available only in English or French · Tested with QGIS 3.40 LTR only; other versions 'should work' but are untested · Model-generated descriptions may be inaccurate and need expert checking · Licence conflict: DOCS state GPL-3, ENTRY metadata states MIT; confirm before reuse

Useful for

Use cases llm-inferred

Pull open terrain, land-cover or hydrology datasets into an open QGIS project for early site screening, checking each dataset's licence first · Run repeatable Processing steps (e.g. clip, buffer, reproject) on project layers, approving each step before it changes data · Style constraint layers and build print layouts for flood or drainage option plans

Audience llm-inferred

GIS analysts · flood consultants · drainage engineers · hydrologists · ecologists · planners

Limitations

Constraints docs-verified

Hosted AI service: no offline mode and no local model, so an internet connection is needed · Answers come from an AI model and can be wrong; review every change before accepting · Each message plus a project description (CRS, canvas extent, layer names, types, field names) is sent to TerraLab's hosted service in the EU · Requires QGIS 3.28 or later · UK-specific coverage of the open data catalog is not stated · Hosted service is not licensed for reuse and text and data mining rights are reserved

Useful for

Use cases llm-inferred

Terrain and catchment analysis workflow guidance in QGIS for drainage or flood risk baselines · GDAL, GRASS and SAGA command guidance for DEM and raster processing · PyQGIS script generation for batch clipping or reprojection of site and boundary layers · Discovery of global geodata sources for early-stage project area baselines

Audience llm-inferred

GIS analysts · hydrologists · flood consultants · drainage engineers

Limitations

Constraints llm-inferred

Provides assistance and tutorials rather than a dataset or API · Interaction text and QGIS environment information (version, view extent, layer metadata) are collected to improve service quality · Screenshot feature is optional and disabled by default · No data coverage, resolution or update frequency stated in the docs · Depends on QGIS desktop installation

Useful for

Use cases llm-inferred

Generate a PyQGIS Processing algorithm that batch-summarises vector layers in a project for drainage or flood-risk data QA · Build a QGIS plugin that exports feature counts and attribute summaries from site or survey layers to CSV · Create a map-tool plugin for measuring or marking features on a site plan

Audience llm-inferred

GIS analysts · GIS developers who script in PyQGIS · Drainage engineers and hydrologists who need bespoke QGIS tools

Limitations

Constraints docs-verified

Not a standalone GUI or CLI; it is a knowledge base and validator that an AI agent runs · Targets QGIS 4 and PyQt6 only; QGIS 3 code is not the intended output · Tested against QGIS 4.0.2 on Windows · Automated testing of plugin GUIs is not yet available; GUI behaviour must be checked manually in QGIS · Generation stops after 3 failed fix attempts and reports the blocker

Useful for

Use cases llm-inferred

Reproducible FRA or drainage analysis packaged as a project.yaml and pipeline.py so a reviewer can rerun it · Discovering and assessing open geospatial datasets for a site constraints screen · Reviewing PostGIS or DuckDB spatial queries for catchment or constraint overlays · Building an interactive map dashboard to share options with a client or planner

Audience llm-inferred

GIS analysts · hydrologists · drainage engineers · flood consultants · planners · ecologists

Limitations

Constraints llm-inferred

Guidance skill, not a data source: output quality depends on the agent and on the data it finds · Docs show no UK-specific sources; examples are NYC and Tartu · Building the Pages site needs Python project dependencies, Node 20+ and npm · Install needs git, nodejs and npx already present · Existing v1 manifests with a map must declare presentation.map.basemap.kind · Default basemap fallback relies on goplex.ee Protomaps tiles · Docs text is truncated at the end, so some content may be missing

Useful for

Use cases llm-inferred

Check whether two Sentinel-2 scenes from different seasons can support a changed-hectares claim before any pixel arithmetic · Verify CRS and units before reporting flood extent or catchment area figures · Audit spatial leakage before reporting validation scores for a flood or susceptibility model · Confirm DEM and terrain-hydrology preconditions before reporting flow-path outputs

Audience llm-inferred

GIS analysts · remote sensing analysts · hydrologists · flood consultants · geospatial developers building AI agent workflows

Limitations

Constraints docs-verified

Behaviour figures come from one runtime and model pair (Claude Code 2.1.214/2.1.222, claude-sonnet-5) and are not universal · Behaviour figures are model-judged, uncalibrated and not yet human-verified · The repository's own Phase 3 quality gate fails: 4.3% critical failures and 19.6% full-criterion pass rate · Known routing defects: 1 false positive, 4 false negatives, 1 incomplete route and 11 execution errors · Routing shows which skill loaded, not whether the answer was correct · Contains no data feeds or UK-specific datasets; it supplies method guidance only · ENTRY kind is 'mcp' and its tools list names skills, but the docs describe Agent Skills rather than an MCP server

Useful for

Use cases llm-inferred

Buffer watercourse or site-boundary layers for stand-off or flood-zone mapping using native:buffer · Clip regional GIS datasets to a site boundary before drainage or civils analysis · Reproject client layers to a common coordinate system (e.g. British National Grid) before combining them · Script a repeatable multi-step geoprocessing pipeline and run it across many sites

Audience llm-inferred

GIS analysts · flood consultants · drainage engineers · developers using AI coding agents

Limitations

Constraints docs-verified

Only tested end-to-end on QGIS 3.44.9 / Windows 11 · Only buffer, clip and reproject have verified templates and tests · Requires a local QGIS installation; not a hosted data service · On Windows, must be called via qgis_process-qgis-ltr.bat rather than the .exe directly

Useful for

Use cases llm-inferred

Agent-driven thematic map production in QGIS for consultancy report figures · Automating repetitive QGIS symbology and layout steps for flood or drainage assessment outputs · Scripted spatial analysis steps run from an AI agent inside a local QGIS session

Audience llm-inferred

GIS analysts · flood consultants · drainage engineers · planners

Limitations

Constraints llm-inferred

Requires QGIS running with the plugin loaded (llm-inferred) · Requires a local OpenClaw installation for the skill component (llm-inferred) · The supplied DOCS describe a different project (GeoBot, a prototype/transition build), so this entry's own functionality is not verified against its documentation

Useful for

Use cases llm-inferred

Buffer and tag site or watercourse features on a map during constraints review · Query ingested drainage or flood reports (PDF/DOCX) via RAG for design criteria lookup · Run LLM analysis locally via Ollama on sensitive project data · Combine custom MCP geospatial tools with map-based analysis

Audience llm-inferred

GIS analysts · hydrologists · drainage engineers · flood consultants · planners

Limitations

Constraints docs-verified

No prebuilt binaries yet; must build from source with Node.js 22+ and npm · Native modules (better-sqlite3, keytar) need platform build tools · SpatiaLite geospatial data operations are still in progress · Agentic Python/TypeScript workflows and the plugin system are planned, not shipped · Windows builds need Visual Studio Build Tools; Linux needs build-essential, python3, libsecret-1-dev

Useful for

Use cases llm-inferred

Flood-risk screening: shortlist DEM, rainfall and exposure datasets in GEE for a hill-catchment AOI · BNG habitat baseline: Sentinel-2 NDVI composite for a site AOI, exported to Google Drive · Drainage strategy: GEE rainfall grid extraction for an AOI as a design-input check

Audience llm-inferred

GIS analysts · hydrologists · flood risk consultants · drainage engineers · ecologists

Limitations

Constraints llm-inferred

ENTRY states no credentials documented, but DOCS describe Earth Engine authorisation and project-level quota checks · Datasets are accessed through Google Earth Engine; the plugin does not host data itself · Earth Engine project quotas and usage limits apply · GeoMaster is bundled as a skill snapshot, not a live-synced repository, so it may drift from upstream · Install examples are Windows/PowerShell-focused

Useful for

Use cases llm-inferred

County-level flood exposure screening for Kenya using Sentinel-1 SAR flood data combined with WorldPop population · Rainfall (CHIRPS) and elevation (SRTM) context for a Kenyan drainage or civils scoping note · Ranked county climate-risk brief with cited Kenyan source documents

Audience llm-inferred

climate risk consultants · hydrologists · GIS analysts · development planners

Limitations

Constraints llm-inferred

Scope is Kenya only per docs, so not applicable to UK projects (ENTRY regions says Global) · County boundaries are a Voronoi approximation, not official geometry · Fallback mode returns deterministic placeholder values, not real measurements · Live results need Earth Engine authentication and a Gemini API key · Decision-support only, not an emergency-response system · Replica of a pattern, not Google's gated Geospatial Reasoning agent · Requires Python 3.11+ and a local install · ENTRY licence is Other while docs state MIT for source code; knowledge-base documents keep their own licences · ENTRY lists no tools; tool names here come from the DOCS architecture diagram (wrapped names rejoined) and argument names are not documented