Planning and site assessments

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

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

Inspect and bounded-query a public ArcGIS FeatureServer or OGC endpoint, then map it in MapLibre for a site-constraints review · Build a styled 2D map of WMS or WFS layers as an EIA or planning baseline, using the same typed client for each protocol · Scan an existing ArcGIS web app for classic widgets and migrate it to MapLibre before the ArcGIS JS 6.0 removal · Give a coding agent typed access to live geospatial endpoints for scripted data checks

Audience llm-inferred

GIS analysts · web and GIS developers · geospatial data engineers · planners and ecologists working with agent-assisted queries

Limitations

Constraints llm-inferred

Release status is beta (0.2.2); 26 experimental subpaths may change before 1.0 · The README tracks the development branch; the npm artifact may not include every described capability · It is a client SDK and supplies no datasets itself; coverage depends entirely on the endpoint queried · Entry metadata lists region as Global, and nothing in the DOCS is UK-specific · Server-attach capabilities (8 of 36 claims) need a Honua Server · The columnar data plane is experimental, the Cesium scene surface is beta and Kepler.gl is experimental · Multi-source service roots need an explicit sourceId · Unsupported capabilities throw HonuaCapabilityNotSupportedError · The map path needs maplibre-gl installed as a peer dependency · MCP transport and tool names are not stated in the supplied DOCS

Useful for

Use cases llm-inferred

Short-term rainfall and snowfall forecast context for earthworks and construction weather-window planning · Soil moisture and reference evapotranspiration (ET₀) inputs for ecological or water-balance screening · Wind gust and precipitation checks for site risk assessments (crane lifts, temporary works, exposed drainage)

Audience llm-inferred

drainage engineers · hydrologists · flood consultants · geotechnical engineers · ecologists · construction and site managers

Limitations

Constraints llm-inferred

Forecast-oriented: DOCS describe forecasts up to 16 days; historical archive is not described on this page (ENTRY says separate historical APIs exist) · Past-data access is via archived forecasts through the Past Days feature, not observed records · Resolution and variable availability depend on the chosen weather model · No UK-specific model is named in DOCS · Commercial use needs a paid subscription · Service terms apply in addition to CC BY 4.0 data licence

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

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

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

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

Active-travel and walking route options along rivers and green corridors for a site access assessment · Indicative public-access path mapping to nearby parks and waterways for planning-stage site context · Sketching GPX/GeoJSON walking routes for site walkover or public-consultation material

Audience llm-inferred

planners · GIS analysts · ecologists

Limitations

Constraints llm-inferred

Walking route tool only; provides no river level, flow or other hydrological data despite the hydrology category · Requires self-hosting with Docker (about 8 GB disk and 4 GB RAM); not a hosted service · First setup takes roughly 20–60 minutes to import OSM data and build tiles · Default region is Greater London; other areas need OSM_REGIONS reconfiguration · Scenic weighting is a soft preference and cannot guarantee routes pass through scenic areas · Public deployment needs extra setup (nginx API key or Cloudflare Tunnel); default ports bind to localhost

Useful for

Use cases llm-inferred

5-day hourly and 15-day daily weather forecast context for site programme and works planning · air quality forecast checks for dust-sensitive construction activities · growing degree days and frost stress days to inform planting or seeding windows for landscape and habitat works · geocoding site names to lat/lon to feed coordinates into other tools

Audience llm-inferred

civils engineers · planners · ecologists · GIS analysts

Limitations

Constraints llm-inferred

forecast products only; DOCS describe no historical data series · a separate API key is needed per service, and only the services in use need keys · ENTRY auth metadata omits POLLEN_API_KEY, which DOCS list · forecast horizons are fixed per service (e.g. 5 days hourly, 4 days air quality) · regions are Global per ENTRY metadata; UK-specific coverage is not stated · ENTRY metadata lists no tools, so tool names cannot be verified from the provided material

Useful for

Use cases llm-inferred

Current conditions check by town or city for a site visit or fieldwork day · Weather context lines for a site or planning report (current conditions only) · Quick weather lookup for a project team briefing

Audience llm-inferred

ecologists · site engineers · planners · project managers

Limitations

Constraints llm-inferred

Single tool (current_weather) that takes only a city name, with no coordinates or site-level input · Current conditions only; no forecast, historical or rainfall-series tools are documented · No hydrological, river or flow data · Depends on a third-party WeatherAPI key · Docs give no rate limits, uptime or data-quality details

Useful for

Use cases llm-inferred

Find a geocoding or reverse-geocoding MCP server to convert site addresses to coordinates for a planning appraisal · Identify a PostGIS or STAC/imagery MCP server to query spatial datasets for catchment or land-use analysis · Locate a weather MCP server to pull rainfall or climate context for a drainage strategy desk study

Audience llm-inferred

GIS analysts · hydrologists · drainage engineers · flood consultants · planners · developers building MCP-based geospatial tooling

Limitations

Constraints llm-inferred

Lists servers rather than providing data itself · Server health varies: 18 stale and 2 pending at the time of the health check · Health status reflects only repository push activity within 12 months · Some entries have URLs still to be confirmed · Access tiers differ by server, and many are commercial or paywalled

Useful for

Use cases llm-inferred

Current-conditions check for weather-sensitive site works planning · 5-day forecast to schedule site walkovers or field surveys · Recall of recent weather queries for a project record

Audience llm-inferred

site managers · civils engineers · environmental consultants

Limitations

Constraints llm-inferred

Requires an OpenWeatherMap API key in WEATHER_API_KEY · Free tier stated as 1,000 queries per day · Needs Docker, PostgreSQL and Redis running for the documented setup · Manual Claude Desktop config edits with local absolute paths · No resolution, history time span or refresh interval documented · Not a source of design rainfall or hydrological statistics · Tool argument schema not documented in DOCS · Docs are in Portuguese

Useful for

Use cases llm-inferred

Air quality baseline (PM2.5, PM10, NO2) for an EIA or planning air-quality section · Rainfall, wind and temperature history over a date range to support site monitoring or construction-weather reporting · Current weather context for a site visit or field-survey log · Timezone-correct timestamp conversion for consultancy field records

Audience llm-inferred

environmental consultants · air quality specialists · drainage engineers · civils engineers · planners

Limitations

Constraints llm-inferred

Location is a city name in English only; no coordinate or site-level input is documented · Data is city-level, not site-specific, so not suitable for site-scale design inputs without validation · Depends on the third-party Open-Meteo API being available · SSE mode is described as legacy; streamable HTTP is the modern option · Not UK-focused in metadata (regions: Global); no UK-specific data sources or stated accuracy · No stated beta status, rate limits or SLA

Useful for

Use cases llm-inferred

Hourly precipitation intensity and rain probability for scheduling site works or concrete pours · Real-time and 7-day weather context for site visit and fieldwork planning · 24-hour historical weather record to support site condition or incident notes

Audience llm-inferred

civils engineers · drainage engineers · environmental consultants · planners

Limitations

Constraints llm-inferred

Requires a Caiyun Weather API key · Coordinates only (lng/lat); no place-name lookup in documented parameters · Historical data limited to the past 24 hours · ENTRY regions lists China only; UK coverage not stated in docs · AQI standards documented are China and USA only; no UK AQI listed · No rate limits, SLA or pricing documented · Hosted server and local install both depend on third-party API availability

Useful for

Use cases llm-inferred

Short-range weather check for scheduling field surveys (ecology, topographic, ground investigation) · Daily precipitation outlook for planning concrete pours, earthworks or dewatering windows · Hourly temperature and conditions for site working-hours planning · Weather context section for project progress or site diary reports

Audience llm-inferred

civils engineers and site managers · environmental consultants · ecologists planning field surveys · project managers

Limitations

Constraints llm-inferred

Forecast only; historical weather data is listed as a future enhancement, not currently offered · Hourly forecasts cover only the next 12 hours; daily forecasts cover up to 15 days · Location input is a city or location name; coordinate input is not documented · Requires an AccuWeather API key and Node.js 18 or later · Weather alerts are a future enhancement, not currently offered · No spatial resolution or update frequency documented; not a substitute for rainfall gauge or river level data

Useful for

Use cases llm-inferred

Current conditions and 1-14 day forecast for site visit or fieldwork planning · Historical weather context for antecedent conditions in a site or drainage narrative · Air quality and sunrise/sunset data for construction-hour and monitoring-visit planning

Audience llm-inferred

civils engineers · drainage engineers · environmental consultants · planners

Limitations

Constraints llm-inferred

Data source and coverage are not stated in the docs; the catalogue lists Global, but UK-specific data is not evidenced · No gauge-based river flow or rainfall-measurement data; not a substitute for hydrological monitoring records · Requires a WeatherAPI key, so usage limits and costs follow that provider · Tool names, parameters and rate limits are not documented · Docs and badges reference devilcoder01/weather-mcp-server, while the catalogue URL is sjanaX01/weather-mcp-server; confirm the source repository · Install steps use placeholder paths (yourusername/Weather_mcp_server) and require Python 3.13+ and uv · Described as a simple, minimal project; maintenance status is unknown

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

Day-of and 3-4 day weather checks for China site works scheduling · Resolve Chinese district/county names to standard city names for project location records · Weather context for fieldwork planning on mainland China projects

Audience llm-inferred

civil engineers · site managers · project planners · GIS analysts

Limitations

Constraints llm-inferred

Mainland China cities only; not relevant to UK-focused work · Requires a valid Amap API key in AMAP_API_KEY or requests fail · Amap API may apply request-rate limits · Forecast horizon is only 3-4 days · No historical weather data offered · Docs' Python client snippet may not match the real MCP client API; confirm tool names via tools/list

Useful for

Use cases llm-inferred

Short-term forecast check for site survey or fieldwork scheduling in Korea · Near-term weather conditions for construction-activity planning in Korea · Quick forecast context for client reporting on Korean projects

Audience llm-inferred

project managers · site engineers · ecologists (fieldwork planning)

Limitations

Constraints llm-inferred

Korea-only data (기상청); no UK coverage, so not relevant to terramcp.earth's UK focus · Requires a personal API key from data.go.kr · Docs describe the project as developed for internal testing · Docs do not state rate limits, historical data, or resolution · Single-developer maintenance contact listed in docs

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

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

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

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

Site context mapping: geocode project addresses and map nearby OSM features (watercourses, schools, parking) for a site walkover pack · Travel planning for site visits: route_fetch and get_route_directions between office and client sites · Distance screening: geo_distance and sort_by_distance to rank candidate sites or monitoring locations by proximity to a reference point

Audience llm-inferred

GIS analysts · planners · environmental consultants · civils engineers needing site context

Limitations

Constraints llm-inferred

Rate limits apply: DOCS give defaults of Nominatim 1 rps, Overpass 2 per min, OSRM 100 per min, adjustable by flags · Data is OpenStreetMap-based; completeness and currency of tags are not described in DOCS · No UK-specific datasets, coverage statements or UK data sources are described in DOCS · Local install required: download a binary or build from source (Go 1.24+) · No hydrological, flood, drainage or ground data offered; not a substitute for authoritative UK datasets · Source of price data used by analyze_neighborhood is not described in DOCS · Coverage is inferred from ENTRY regions, not stated in DOCS

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

Cloud-free dry-season NDVI/NDWI baseline for an ecology or BNG habitat assessment · Land-cover training polygons from ESA WorldCover for a site-scale classification · Area-wide vegetation and water-index statistics for a catchment or planning screening report

Audience llm-inferred

GIS analysts · ecologists · hydrologists · planners

Limitations

Constraints llm-inferred

Requires Python 3.10+, a Google Earth Engine account and a Google Cloud project with the Earth Engine API enabled · Earth Engine access is free for research and non-commercial use; commercial consultancy use needs checking against Google's terms, which DOCS do not address · execute_code runs arbitrary Python on the local machine with the user's Earth Engine login; do not expose the server to untrusted clients · Initial earthengine authenticate step opens a browser · Roadmap features not yet available: Dynamic World and Hansen training labels, consensus logic, shapefile/KML/GPX/CSV import, local GeoTIFF backend, OpenStreetMap ingest, STAC backend, change-detection helpers · Land-cover classification workflow needs the optional lulc-engine package · No UK-specific datasets (e.g. river gauges, LiDAR DEM) are documented; these would need to be found in the Earth Engine catalog or added via execute_code · Spatial and temporal resolution and update frequency are not stated · Maintenance status and version history are not documented

Useful for

Use cases llm-inferred

Regional land-cover and environmental statistics for a site boundary during desk-based appraisal · Mapping satellite-derived layers in chat for planning or ecology baseline review · Screening dataset availability in Earth Engine before building a GIS workflow

Audience llm-inferred

GIS analysts · ecologists · hydrologists · planners · environmental consultants

Limitations

Constraints llm-inferred

Requires Earth Engine account and Google Cloud service account credentials with private key · SSE transport requires a Redis instance · Deployment on Vercel expects Fluid compute and an adjusted maxDuration · Presented as a sample app built on the Vercel MCP adapter, so production readiness is unverified

Useful for

Use cases llm-inferred

Check whether a Saharan dust episode is affecting site air quality before dust-sensitive construction works · Pull regional SO₂ and PM2.5 background context for an air quality assessment in Central Europe · Compare pollutant time series across up to 5 cities for a planning or consultation report

Audience llm-inferred

air quality consultants · environmental consultants · planners · GIS analysts

Limitations

Constraints llm-inferred

Coverage is Central Europe (44–56°N, 2–18°E). Most of the UK lies west of 2°E, outside this area. · Modelled CAMS data at ~10 km resolution, not site monitoring. The registry auth field lists CAMS_API_KEY, but the docs say the MCP server needs no key. · Depends on the daily GitHub Actions job and the data-latest release; outages upstream would stop updates. · Runs as a local install (uv, cloned repo) inside Claude Desktop or Cursor, so it needs a desktop MCP client. · Parameter schemas for the MCP tools are not documented in DOCS.

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

Ground-station visibility windows for satellite data downlink planning · Satellite revisit and coverage footprint analysis for earth-observation survey planning · Orbit lifetime and conjunction screening for satellite-dependent sensing assets

Audience llm-inferred

satellite mission analysts · space systems engineers · GIS analysts (earth-observation planning)

Limitations

Constraints llm-inferred

Satellite/astrodynamics scope; no UK water, civils or environmental datasets · COM propagation fix is Windows-only; Linux/macOS get Connect TCP only · Without COM, conjunction and access results may be incomplete · acat_set_threat_volume is unsupported and changes no settings · Nonzero sample_step_size is rejected · Catalogue tool names (e.g. set_tle) do not match documented tool names (stk_orbit with action set_tle) · Requires an external AGI STK installation with Connect enabled

Useful for

Use cases llm-inferred

Ground station visibility passes (azimuth, elevation, range) for a satellite comms or telemetry planning note · Ground track and 3D orbit figures for a report or client presentation · Converting orbital elements from a dataset to Cartesian state for downstream analysis

Audience llm-inferred

GIS analysts · remote sensing analysts · space-systems engineers

Limitations

Constraints llm-inferred

Some features depend on bundled Windows .exe programs, so they may not run on other platforms · Requires Python 3.13 or higher and the uv package manager · Orbital mechanics only; no water, civils or environmental datasets, and no UK-specific data · Not a hosted service; must be cloned and run locally · Orbit computations are not documented as validated for engineering or regulatory use

Example tool calls docs-verified

{
  "tool": "kpl2cts",
  "arguments": {
    "<kepler_elements>": [
      7000,
      0.001,
      45,
      90,
      0,
      0
    ]
  }
}

{
  "tool": "date2mjd",
  "arguments": {
    "<date>": "2025-01-01"
  }
}

Useful for

Use cases llm-inferred

Quantity take-off of doors, windows and walls from an IFC model for BIM coordination · Total wall and surface areas from IFC properties for finishes or coating quantity estimates · Filtering elements by property thresholds (e.g. wall height) for access or equipment planning · Building inventory summary of element types to check model completeness before handover

Audience llm-inferred

BIM engineers · civils engineers · architects · quantity surveyors · facilities managers · developers working with IFC data

Limitations

Constraints llm-inferred

Requires a local Python (and Node.js) environment; server must be started manually · Docs do not state supported IFC schema versions · Scope is querying and aggregation only; no geometry or spatial/GIS analysis described · Docs describe query capabilities as the current scope ('At this point, queries can include...') · No hosted service, rate limits or versioned release policy described · Tool parameter names are not documented in the README

Useful for

Use cases llm-inferred

Generate IFC-correct wall, slab and door/window models for early design option studies · Produce scaled SVG plan and section drawings for coordination or planning-stage review · Set up IfcSpace and IfcGrid with space boundaries for room and area checks

Audience llm-inferred

BIM coordinators · BIM/civils engineers · architectural technologists

Limitations

Constraints llm-inferred

Verified only against Bonsai v0.8.5 and Blender 5.1; other versions are untested · Requires BlenderMCP and a running Blender desktop session to execute the helpers · Known BIM-correctness debt is flagged inline and not fully resolved · MEP, foundations/structural, site context and schedule/COBie exports are not yet covered

Useful for

Use cases llm-inferred

Massing model of a small building from a DXF floor plan for early planning visuals · Volume quantity take-off of walls, slabs and columns, net of door openings, for an early cost check · Exporting glb or obj models of a building for client review in a 3D viewer

Audience llm-inferred

BIM/civils engineers · architectural visualisation modellers · quantity surveyors

Limitations

Constraints docs-verified

Profiles written for Vietnamese house drawings (220 and 110 walls, concrete columns); not UK standards or data · Requires Blender 3.0+ and Python 3.10+ installed locally, with the addon enabled and its connection started · All modelling runs inside Blender via the addon socket on port 9877, so Blender must be open · chay_python runs arbitrary Python in Blender; the safety check is not a firewall, so read the code before running on important drawings · No hydrological, environmental or UK geospatial datasets (no DEM, flow, rainfall) · ENTRY lists no tools and DOCS names only chay_python; the 30-tool list is in docs/cong-cu.md and was not supplied · Independent project, not affiliated with Blender Foundation; maintenance status not stated

Useful for

Use cases llm-inferred

Checking OSM tags on drainage or utility features before importing them into a project GIS layer · Standardising OSM tags on site-context features for a planning or environmental baseline · Converting flat tag text to JSON for scripted QA of OSM extracts

Audience llm-inferred

GIS analysts · developers building LLM or AI assistant tooling · OSM data editors

Limitations

Constraints docs-verified

Proof of concept; a replacement is planned with no date promised · validate_tag detects only ~20% of wiki-deprecated tags · Typos and foreign values are accepted as valid · Answers from schema data only; no network access to OSM · Not a standalone app; needs an MCP client such as Claude Code or Claude Desktop · search_tags has no typo tolerance; multi-word search_presets queries can return nothing

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

Isochrone catchment around a site for accessibility screening (calculate_isochrone) · Snapping survey or GPS points to the OSM road network before analysis (snap_to_roads, map_match_gps) · Checking OSM data quality (OSMOSE issues) in an area before reusing it as a baseline · Route distance and travel-time matrices for site-visit planning (get_distance_matrix)

Audience llm-inferred

GIS analysts · planners · environmental consultants · developers building AI/MCP workflows

Limitations

Constraints llm-inferred

Local install required: Node.js v18 or higher, plus an npm build step · Community project by Grab; no support or SLA stated · Relies on third-party services (Nominatim, OSRM, Overpass, OSMOSE, Taginfo) whose availability and rate limits are not described · Global OSM scope; no UK-specific coverage described · No update frequency, resolution or time span stated · Tool parameter schemas and output formats are not documented in DOCS · Entry lists no tools; tool names are taken from DOCS

Useful for

Use cases llm-inferred

Locate nearby OSM features (parks, facilities) for site context in a planning or ecology desk study · Preview a selected section of a GPX survey track against candidate OSM roads before any edit · Draft reviewed OSM road corrections from on-site surveys, with exact preview and separate confirmation · Check OSM coverage of local assets and add missing POI nodes after duplicate inspection

Audience llm-inferred

GIS analysts · planners · ecologists · civils and survey engineers · OSM contributors

Limitations

Constraints docs-verified

Alpha status; review-first, so nothing is edited automatically · Development sandbox is not a copy of the real map · Production editing needs a separate OAuth app and an MCP host that supports elicitation · Optional Valhalla routing for track matching must be installed manually with regional tiles · Search queries are sent to public OSM services · A single GPS trace is not ground truth · No UK-specific coverage or data freshness is stated in the docs · Requires Python 3.10+ and uv for the uvx launch

Useful for

Use cases llm-inferred

EIA/planning ecological baseline: seasonal home range (MCP/KDE) and range contraction for a species affected by a scheme · Water-proximity assessment: distance to water by behavioural state (fig7) to inform mitigation near abstractions or drainage features · GIS hotspot layers: clusters.geojson for habitat mapping in QGIS or ArcGIS

Audience llm-inferred

ecologists · environmental consultants · GIS analysts · planners

Limitations

Constraints llm-inferred

Docs describe a command-line pipeline (python run.py config.yaml); no MCP server interface, transport or callable tool names are documented · The ENTRY tools list contains output filenames, not callable MCP tools · Tested only on African lions, mountain caribou and African elephants · Requires Python 3.10+ and a local install; HDBSCAN is an optional extra · KDE can be slow on large datasets; reduce kde_max_pts or kde_grid_size · Water-based outputs (fig7, fig10) require a water_path input · Input columns must match config mappings exactly (case-sensitive) · Degenerate clustering (all noise, single cluster, >85% noise) needs config tuning

Useful for

Use cases llm-inferred

Scope 1 to 3 carbon footprint for a UK consultancy project using DEFRA and Ember UK grid factors · Scope 1 site-works emissions from plant and fleet diesel records · Embodied carbon screening of construction materials using DEFRA material factors · Client GHG inventory for ESG or planning-stage carbon reporting

Audience llm-inferred

environmental consultants · civils and construction sustainability teams · ESG consultants · climate tech developers

Limitations

Constraints llm-inferred

Carbon accounting only; no water, flood, hydrology or ground data · Spend-based Scope 3 uses USEEIO, which is US NAICS-based, so UK spend coverage is weak · Factor vintages and database version dates are not stated in the docs · Entry tools list includes Python dependencies (pydantic, pint, pandas, plotly, fastmcp, jinja2) that are not MCP tools; the documented MCP tools are the 8 named in the docs · Entry licence is null but docs state MIT · Requires a local Python 3.11+ and uv install; no hosted endpoint is documented · Accuracy depends on input data quality (docs)

Useful for

Use cases llm-inferred

Desk-based site context screening: geocode an address, buffer 1-2 km, then pull OSM features (e.g. waterways, buildings) for a constraints check · Preliminary civils or drainage gradient checks: elevation profile along a proposed route or corridor · Terrain screening: sample and zonal stats of a client-supplied GeoTIFF DEM over a site boundary · Drive-time accessibility isochrones for planning or appraisal reports (requires OpenRouteService key)

Audience llm-inferred

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

Limitations

Constraints docs-verified

Release status: PyPI provides v0.3.0; the v0.4.0 release candidate (newest provider and hardening work) is not yet released · Default public providers have usage policies: Nominatim max 1 request/second, OSRM demo server not for production, Overpass fair use · Isochrones require GEO_MCP_ORS_API_KEY, which is unset by default · Docs are inconsistent on tool count (44 in places, 42 in CLI output) · Roadmap items not yet available: Mapbox/Google geocoding, WebSockets, batch file processing, reproject/clip/mosaic · No UK-specific datasets or hydrological time-series (gauge levels, rainfall) documented · Raster and vector tools operate on local files supplied by the user; no bundled datasets documented

Example tool calls docs-verified

{
  "tool": "geocode",
  "arguments": {
    "query": "Brandenburg Gate, Berlin"
  }
}

{
  "tool": "buffer",
  "arguments": {
    "point": {
      "lat": 52.5163,
      "lon": 13.3777
    },
    "distance_m": 1000
  }
}

Useful for

Use cases llm-inferred

Export print-quality layouts and Map Series from an ArcGIS Pro project for consultation or planning reports · Run clip, buffer or intersect geoprocessing on site or catchment layers and add outputs to the live map for review · Query layer attributes to build constraint or receptor tables for an assessment · Let an agent assemble and symbolise a thematic map in the open project while the consultant watches

Audience llm-inferred

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

Limitations

Constraints docs-verified

Requires a licensed ArcGIS Pro install; no ArcPy outside Pro · Live bridge needs the .NET add-in built and installed in Pro, plus MCP registration · Verified only on ArcGIS Pro 3.4 / ArcPy 3.4.3 / .NET 8 · Cartographic authoring (symbology, layout, layer management) is still an open frontier on the roadmap · Noncommercial licence; commercial use needs a paid licence · Tool arguments and parameter names are not documented in the README

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

Pull constraint or asset layers from a client's ArcGIS REST services into a site screening report · Run a point-in-polygon check of a site coordinate against a council or utility layer · Generate a shareable Leaflet map of selected layers for a client or planning review · Inventory layers, service names and geometry types across an ArcGIS server before building an integration

Audience llm-inferred

GIS analysts · planners · environmental consultants · civils engineers · developers building ArcGIS integrations

Limitations

Constraints llm-inferred

Only FeatureServer services are processed; MapServer and other service types are skipped · Described by its author as a side project, used as-is, with no support commitment · Results capped by max_features (default 100 for queries, 1000 for maps) · Requires a configured config.yaml with service base_url and HTTP headers before use · Not UK-specific; the example configuration targets a Jerusalem municipal service · Metadata tools field lists parameter names and file names rather than the five exposed tool names

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

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

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

Site access route and drive-time checks for field survey visits · Speed limit and route safety review for fleet or site logistics · Cleaning GPS survey-vehicle traces by snapping them to roads · Elevation gain profiling of routes for site walkover planning

Audience llm-inferred

GIS analysts · civils engineers · planners · environmental consultants

Limitations

Constraints llm-inferred

Requires a Google Maps Platform API key and the relevant Google APIs enabled in the Cloud project · Search radius capped at 50000 m by default configuration (MAX_RADIUS_METERS) · Results limited to 1-60 per query (MAX_RESULTS) · Data is Google's; docs give no UK-specific coverage or accuracy statement · No update frequency or data resolution stated in docs

Useful for

Use cases llm-inferred

Drive-time and distance estimates between project office and site for travel planning · Geocoding client or site addresses to coordinates for GIS layers · Comparing alternative routes for plant or materials haulage

Audience llm-inferred

GIS analysts · civils engineers · planners

Limitations

Constraints llm-inferred

Requires a Google Maps Platform API key in GOOGLE_MAPS_API_KEY · Runs from a local clone via npx ts-node; no hosted endpoint is documented · Tool names and schemas are not listed in DOCS or catalogue metadata (tools: []) · Google API quotas and billing are not described in DOCS · No licence stated in catalogue metadata · Not UK-specific; routing and geocoding depend on Google's coverage · Maintenance status and update cadence are not stated

Useful for

Use cases llm-inferred

Geocode site and property addresses to coordinates for desk-based site assessments · Find nearby schools, hospitals and other receptors around a development site for sensitivity screening · Estimate driving and walking routes and times from a site to access points or facilities for transport appraisal

Audience llm-inferred

GIS analysts · planners · transport and highways consultants · civils engineers

Limitations

Constraints llm-inferred

Requires a Huawei Map Kit API key (authentication needed) · Coverage area and data quality are not documented; UK coverage is unverified · Rate limits and API quotas are not documented · Map Kit is a Huawei service, so its data sources and licensing terms for commercial use are not described in the docs · No spatial or temporal resolution or update frequency documented · Examples in the docs are Chinese-location focused

Example tool calls docs-verified

{
  "tool": "geocode",
  "arguments": {
    "address": "10 Downing Street, London"
  }
}

Useful for

Use cases llm-inferred

Screen a candidate development site by counting nearby amenities and competing businesses within a 15-minute walk · Provide accessibility context for a transport or planning statement using isochrones and routes from a site · Build a desk-based context pack for a site: nearby land use, buildings and transit stops · Audit nearby playgrounds and parks for a recreation or community baseline

Audience llm-inferred

planners · GIS analysts · transport planners · environmental and civils consultants (desk-based context) · agent developers building spatial assistants

Limitations

Constraints docs-verified

No live traffic, no opening hours, no ratings or photos · Recreation-layer rows have no confidence or operating_status and are often unnamed (name may be null) · Places query latency increases with the recreation layer enabled (second dataset scan per query, cached) · Overture and OSM data is open crowd and business-listing data, not surveyed or authoritative baseline data; no flood, hydrology or drainage datasets are documented · Attribution to Overture Maps and OpenStreetMap contributors required for user-facing outputs

Useful for

Use cases llm-inferred

Pre-visit check of road closures and chain controls for US fieldwork sites in covered states · Haulage and site-access route risk screening for US civils projects using live incidents and closures · Wildfire perimeter and road closure context for US environmental site assessments · Travel-time and toll cost estimates for US consultancy site visits

Audience llm-inferred

environmental consultants (US fieldwork logistics) · civil engineers and site planners (US projects) · GIS analysts · general AI assistant users

Limitations

Constraints llm-inferred

US road data only; no UK coverage · Coverage is uneven across the 37 states, and some states offer only roadwork or nothing usable · California-only detail (CHP dispatch logs, per-lane closures, chain-control levels, CAL FIRE perimeters) · Feed failures are served as last-good data flagged stale, so data can be out of date · Watch-area accounts require approval · Self-hosting is not supported by the author · Premium features are planned for the hosted app · Conditions change faster than feeds; not a substitute for official road information

Useful for

Use cases llm-inferred

Pull Berlin environmental, traffic and geodata records (Umwelt, Verkehr, Geo categories) as baseline inputs for Berlin-based site assessments · Locate resource download URLs for Berlin datasets to feed GIS or hydrology workflows · Check dataset licence and recency before reusing Berlin data in client reports

Audience llm-inferred

GIS analysts · planners · environmental consultants · hydrologists · civils engineers working on Berlin projects

Limitations

Constraints llm-inferred

Berlin-only scope; the 'Global' region tag in the entry overstates coverage · Catalogue only, with no DataStore: data must be downloaded from resource URLs · Dataset licences vary, so each record's licence must be checked before reuse · Local use needs uv and a Python install; remote SSE mode needs self-hosting · Docs state no rate limits or uptime guarantees, and the server depends on upstream CKAN availability · Docs and tool descriptions are in German · Dataset file formats are not specified in the docs

Useful for

Use cases llm-inferred

Nearby recent bird records within a set radius of a site for ecological baseline context in an EIA or planning appraisal · Checking recent records of a target species near a proposed development footprint using ebird_get_nearby_observations_for_species · Identifying birding hotspots near a site to inform survey location or access planning

Audience llm-inferred

ecologists · ecological consultants · planners · GIS analysts

Limitations

Constraints llm-inferred

Requires an eBird API key, supplied via --api-key or the EBIRD_API_KEY environment variable · Results capped by maxResults (default 100) and look-back window (back, default 14 days) · Provisional observations are included by default (includeProvisional default true) · Requires Node.js v14 or later · Setup instructions focus on Claude Desktop; other MCP clients use a separate install script · No rate limits or data update frequency stated in docs · Entry metadata 'tools' field lists parameter names (e.g. back, maxResults), not tool names

Useful for

Use cases llm-inferred

Pre-development bird baseline from recent and historic observations near a site (ecology scoping) · Notable/rare species check within a search radius for ecological constraints screening · Species-specific occurrence records for habitat assessment context · Hotspot identification to inform bird survey planning

Audience llm-inferred

ecologists · ecological consultants · environmental planners

Limitations

Constraints llm-inferred

Requires an eBird API token; ENTRY auth field is null but docs say a token is needed · Docs have the token hard-coded in server.py (line 15), so the token sits in source code · Requires Python 3.12+, uv or pip, git, and Claude Desktop (local install) · Claude Desktop config examples are given for Windows and Mac-OS only · Region codes must be valid or no data is returned · UK coverage is not stated in the docs · No rate limits, resolution or update frequency documented

Useful for

Use cases llm-inferred

Tide and surge levels at Dutch coastal sites for marine works or outfall boundary checks (tides_nl) · Wind and wave forecast windows for coastal survey or dredging campaign planning · Bridge clearance and fairway depth checks for barge or crane access routes (fairway_nl)

Audience llm-inferred

coastal and marine engineers · hydrologists · civils and BIM engineers planning marine logistics · GIS analysts

Limitations

Constraints llm-inferred

Built and documented for recreational sailing, not engineering or regulatory use · Official charts, almanacs and notices must be checked before relying on outputs · Windy, WorldTides, Stormglass and AISStream need user-supplied API keys; keyed tools only appear when the key is present · AISStream is community-fed and sparse mid-ocean · Some bridges may show '(name unknown)' where OSM has no nearby named bridge · All tool times are UTC · Depends on third-party public endpoints (RWS, NDW, OSM/Overpass, aviationweather.gov, Open-Meteo) with no stated SLA · No public hosted endpoint is documented; the user must run or host an instance (docs use a 'your-host' placeholder) · ENTRY metadata lists OAuth, but DOCS describe API-key URL parameters and state 'No OAuth required' for Claude.ai · Likely single-maintainer personal project ('Built by @ai_kulikov'), so maintenance risk

Useful for

Use cases llm-inferred

Diagnosing slow response times on a client-hosted PHP permit or planning portal using get_traces · Tracking error and exception counts on an internal PHP data-submission tool using get_issues · Reviewing daily performance trends for a PHP web service during a site-monitoring handover

Audience llm-inferred

web developers maintaining PHP applications · DevOps and platform engineers · digital teams running client-hosted web services

Limitations

Constraints llm-inferred

Not an environmental, hydrological, civils or geospatial data source; it is APM for PHP applications, despite the 'environment' category and 'Global' region in the entry · Only useful where the consultancy operates or hosts a PHP application instrumented by Tideways · Requires a paid Tideways account, plus TIDEWAYS_ORG and TIDEWAYS_PROJECT in addition to the token; the entry's auth field (YOUR_TOKEN) does not match the documented variables · Default rate limit of 2500 requests per hour; docs advise matching it to plan (Standard 1000, Basic 250) · Returns raw JSON without interpretation, so the assistant must do all analysis · Stdio transport only, and not usable as a standalone CLI · Forked from abuhamza/tideways-mcp-server, so upstream maintenance risk should be checked

Useful for

Use cases llm-inferred

Rail corridor context for linear infrastructure route options (distance, operator, rolling stock) · GIS visualisation of rail corridors for planning and stakeholder presentations · Desk-study reference locating major rail corridors near proposed works, using LineString geometry for screening

Audience llm-inferred

GIS analysts · planners · transport planners

Limitations

Constraints docs-verified

Curated notable routes only, not exhaustive · Facts are approximate published values; not for operations · Route counts differ by version: site 1,338, MCP server 1,247, this download 961, Zenodo 744 · Download frozen since 23 July 2026; exporter blocked pending licence split · Geometry partly OSM-traced (ODbL); per-route licence split not yet published · pax_per_year populated for only 80 of 961 routes · Global dataset; UK-specific coverage not stated · Per-route stories, photos and journey guides excluded from this package · url fields still point to trainrouter.com (redirects)

Useful for

Use cases llm-inferred

Reference pattern for grounding AI assistant answers in 3D site or catchment context in a CesiumJS viewer · Prototyping AI-assisted camera control and 3D Tiles/terrain review for planning or drainage schemes · Agent-skill-driven CesiumJS code generation for internal geospatial visualisation tools

Audience llm-inferred

GIS analysts · web developers building CesiumJS apps · BIM and civils engineers reviewing 3D models

Limitations

Constraints docs-verified

Repository is deprecated; active development has moved to cesiumjs-ai-starter-app and cesiumjs-skills · Legacy architecture used a WebSocket bridge needing a separate local server process per user, tied to a single browser tab, and not scalable · No UK-specific or consultancy datasets; coverage is global and it provides integration patterns rather than data

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

Desk-study context: building and land-use composition within a radius of a site · Access and highways screening: nearest road and road class to a site, plus road surface mix · Assigning a site to its admin boundary (region or city) for reporting · Amenity and receptor counts within a radius for environmental or planning baseline notes

Audience llm-inferred

GIS analysts · planners · environmental consultants · civils engineers

Limitations

Constraints llm-inferred

Global dataset with varying regional completeness; not UK-specific · Quarterly release cadence; server pinned to release 2026-01-21.0 by default · Radius capped by MAX_RADIUS_M (default 50000 m) · Hosted SSE/HTTP mode needs an API key; stdio mode does not · Spatial analytics only: no geocoding, routing or map display · Community open-source project; maintenance and support commitments not stated

Useful for

Use cases llm-inferred

Bulk geocoding of site or asset address lists from a spreadsheet · Drive-time and walk-time isochrones for site accessibility and catchment screening · Route and travel-time estimates for site visit or survey planning · Static map images with markers and route overlays for report figures

Audience llm-inferred

GIS analysts · planners · civils and environmental consultancy staff

Limitations

Constraints llm-inferred

Requires a Stadia Maps API key · Must be built locally (bun or npm) before use · Transport type and exact tool names not stated in docs · UK coverage for geocoding, routing and maps not stated; entry region is China · Starter server: tool schemas consume context and tools need tailoring

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

Search the STAC catalog for environmental raster layers to build a site-scale GIS baseline · Retrieve land cover or vegetation layers as inputs to a BNG habitat baseline · Gather historic environmental datasets for planning constraint mapping

Audience llm-inferred

GIS analysts · ecologists · hydrologists · planners

Limitations

Constraints llm-inferred

Dataset-specific licences must be checked before reuse · Asset downloads require signed URLs · No licence recorded in entry metadata · No documentation retrieved, so dataset contents and coverage are unverified

Useful for

Use cases llm-inferred

Screen building heights in GeoJSON against a threshold (e.g. buildings above 50 m) and export the subset for massing or planning review · Render a data layer to PNG/SVG as a quick visual check for AI-assisted review of a dataset · Export layers to CASS-compatible DXF for CAD handover where the client workflow uses CASS

Audience llm-inferred

GIS analysts · civils and BIM engineers · AI agent developers building MCP workflows

Limitations

Constraints docs-verified

Streamable HTTP transport has no authentication or TLS; a reverse proxy and auth are needed for remote exposure · Version 0.1.0; Phase 1 core I/O (FGB, GeoParquet, Shapefile, DXF, DWG read) is still in progress · GPU rendering, vector editing and the WASM gene system are roadmap items, not current features · Docs and examples centre on Chinese cadastral and CAD workflows (GB/T 42547, CASS); no UK data coverage is described · Catalogue licence field reads 'Other' while the docs state MIT OR Apache-2.0; confirm before procurement · Building from source needs Rust 1.94+

Useful for

Use cases llm-inferred

Public transport options for Nordic site visits and consultant travel planning · Nearby stop discovery around a Norwegian/Nordic project site for access assessment · Checking active service disruptions on transit routes before site mobilisation · Geocoding Nordic place names to coordinates for transport-related site inputs

Audience llm-inferred

transport planners · GIS analysts · civils and project engineers working in Norway/Nordics

Limitations

Constraints llm-inferred

Covers Norwegian/Nordic public transport only; not UK coverage despite ENTRY regions listing Global · Described as a proof of concept in the ENTRY metadata · Licence not stated; defers to Entur · Default endpoints are the Entur dev API; production requires the prod profile or env vars · Self-hosted: requires running the Spring Boot server (Maven or Docker) · Service alerts and departures depend on upstream Entur API availability

Example tool calls docs-verified

{
  "tool": "departures",
  "arguments": {
    "stop": "Oslo S",
    "numberOfDepartures": 10,
    "language": "en"
  }
}

{
  "tool": "geocode",
  "arguments": {
    "text": "Grünerløkka",
    "maxResults": 5
  }
}

{
  "tool": "trip",
  "arguments": {
    "from": "Oslo S",
    "to": "Bergen",
    "maxResults": 3,
    "language": "en"
  }
}

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

Offline basemap with 90m/30m contours for site walkover and drainage gradient screening · Nearest-POI screening for field visits (hospitals, pharmacies, fuel, water taps) with named POIs ranked first · Agent-driven route and access-track planning exported as GPX for field teams

Audience llm-inferred

GIS analysts · civils engineers · drainage engineers · ecologists · planners

Limitations

Constraints llm-inferred

Self-hosting required: about 101 GB storage for planet.mbtiles, plus about 290 GB optional for contours · Hiking difficulty and sac_scale data absent on stock OpenMapTiles tiles; routing is not difficulty-aware without the extended profile · drinking_water POIs include springs and troughs and are not a potability guarantee · geocode and reverse_geocode tools are not registered unless PHOTONSERVER is set · analyze_gpx and follow_route are listed in catalogue metadata but are not documented in DOCS · Router is documented as a basic router, not a full-featured one; routing segments capped at 50 km straight-line by default · Single-maintainer project; no maintenance commitments stated