Terrain and elevation analysis

Useful for

Use cases llm-inferred

Discover candidate NASA satellite precipitation or elevation datasets for supplementary catchment context · Check granule availability over a site and date range before scoping a remote sensing data request · Find OPeNDAP or WMS access endpoints for environmental baseline layers · Locate citable publications and DOIs for a dataset used in a technical report

Audience llm-inferred

GIS analysts · hydrologists · environmental consultants · remote sensing specialists

Limitations

Constraints llm-inferred

Global NASA datasets, with no UK-specific coverage stated; coverage must be verified per region · Collections can declare global coverage despite data gaps, so granule checks are needed · The discover_data tool and its ingestion pipeline are legacy and being deprecated · Clients should allow a 60000 ms timeout for complex spatial or temporal queries · Downloads require the earthaccess library and its authentication · No rate limits or service-level commitments are documented

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

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

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

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

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

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

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

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

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

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

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 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

Model QA: list levels and elevations to check floor levels and invert assumptions against drainage or civils design · Parameter completeness check: colour-splash elements by parameter value to spot missing data before issue · Coordination drawings: export named Revit views as images for design review or client markup

Audience llm-inferred

BIM/civils engineers · BIM coordinators · Drainage and civils engineers using Revit · Python developers extending Revit automation

Limitations

Constraints docs-verified

Not yet Autodesk Marketplace certified · Requires desktop Revit running with pyRevit Routes active · Bridge accepts loopback hosts only; remote VM/LAN not supported · Docs status table marks 10 of the listed tools as Pending (e.g. create_line_based_element, delete_elements, modify_element) · Docs say the review candidate has 20 tools, but catalogue metadata lists 30 · pyRevit Routes API is in draft form and subject to change · execute_revit_code runs arbitrary Python; model-changing requests need in-Revit review

Useful for

Use cases llm-inferred

Spot-check EG surface elevations at survey coordinates in an open Civil 3D drawing · Confirm station and offset of survey points against a named alignment such as CL-MAIN · Inventory surfaces, alignments and profiles in a drawing for design QA

Audience llm-inferred

BIM/civils engineers · drainage engineers

Limitations

Constraints docs-verified

Non-official, not from Autodesk; documented as research only · Windows-only (COM automation) · Requires Civil 3D open with a drawing loaded · create_cogo_point is marked work in progress (WIP) · Requires Python 3.11 and pip dependencies (fastmcp, pythonnet, pywin32, pydantic)

Useful for

Use cases llm-inferred

Elevation sampling at site or boundary points to screen drainage and overland flow gradients · Static satellite or terrain maps of a study area with marked monitoring or sampling points for reports · Weather and forecast context for scheduling fieldwork such as sampling or ground investigation · Geocoding site addresses and building a travel-time matrix between survey points for field logistics

Audience llm-inferred

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

Limitations

Constraints llm-inferred

Requires a Google Maps API key and billing-enabled Google Cloud account · Each Google API must be enabled separately; REQUEST_DENIED if not · Quota limits apply; OVER_QUERY_LIMIT when exceeded · Environmental APIs (air quality, solar, pollen, weather) are optional and may have different pricing · Requires Node.js 18+ and a local build (npm install, npm run build) · No UK-specific or hydrological data (river gauges, rainfall, flood maps); general-purpose mapping and environmental context only · Google pricing and quotas can change, so they must be checked before use

Useful for

Use cases llm-inferred

Swiss site access and route appraisal using named hiking routes and elevation profiles · Public transport access check for Swiss field survey visits · Weather window forecasting at Swiss field survey sites for scheduling fieldwork

Audience llm-inferred

GIS analysts · planners · ecologists · field survey coordinators

Limitations

Constraints llm-inferred

Switzerland only; not applicable to UK sites · geo.admin.ch fair use is 20 requests/min on average · transport.opendata.ch has a soft, undocumented rate limit · Open-Meteo data requires CC BY 4.0 attribution · Commons Clause licence restricts selling the software; licence metadata reads Other · Windows binary is unsigned and may trigger SmartScreen; macOS needs a Gatekeeper workaround · Test suite stubs fetch with no committed fixtures; some behaviour was verified only with live probes during initial development · Hiking and weather data are not UK-relevant; not suited to the core UK water and civils workflows

Example tool calls docs-verified

{
  "tool": "forecast",
  "arguments": {
    "lat": 47.2494,
    "lon": 9.3434
  }
}

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

Slope classification of a site DEM to support earthworks and drainage feasibility · Riparian buffer around watercourses, erased from a site boundary before developable area is calculated · Watershed delineation and catchment area from a DEM for drainage strategy inputs · Zonal slope statistics per parcel, plot or zone for site appraisal reporting

Audience llm-inferred

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

Limitations

Constraints llm-inferred

Built for ArcGIS Pro 3.x on Windows; paths and config are Windows-specific · Terrain and raster tools need a Spatial Analyst licence · Runs as a stdio subprocess with one connection per client · arcpy calls are synchronous, so long jobs need a stable ArcGIS Pro connection · Documentation is in Indonesian and the CRS examples are Indonesian (UTM 47-50, DGN95) · No licence information in metadata · Metadata region is Global, but the stated design target is Indonesian palm oil plantation GIS teams

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

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

Cadastral and OEREB public-law restriction check for a Swiss parcel during site appraisal · Elevation profile along a candidate Swiss route or alignment for civils option appraisal · Contaminated-sites and hazard-map screening for a Swiss canton via geodienste.ch layers · Commune and BFS-number lookup to join Swiss project areas to BFS statistics

Audience llm-inferred

GIS analysts · civils engineers · planners · environmental consultants

Limitations

Constraints llm-inferred

Switzerland-only data; provides no UK coverage, so not applicable to UK projects · ENTRY metadata is inconsistent: it says 13 tools while the docs describe 20; its tool list includes output field names (summary, results, count, match_type, is_error), a parameter name (operation) and names not in the docs (swisstopo_feature_lookup, swisstopo_geodata_download); verify tool names against the running server · Version 0.5.0 per docs badge (pre-1.0): maintenance and API stability risk · Depends on external services (Swisstopo, geodienste.ch, Overpass, OpenPLZ); availability not guaranteed · Zoning result is not legally binding (per docs) · Hosted use in browser requires self-deploying the server (e.g. on Render); no hosted endpoint is documented · Time span and spatial/temporal resolution are not documented

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

DEM and orthomosaic production from drone survey photos for site topographic baselines · Ground-classified point clouds and surface models from UAV photogrammetry for earthworks or cut-fill inputs · Survey-grade models controlled with ground control points and coded markers · Batch export of DEM, orthomosaic and point cloud deliverables as GeoTIFF or LAZ for GIS and BIM handover

Audience llm-inferred

drone survey and photogrammetry consultants · GIS analysts · civils and BIM engineers · terrain and heritage 3D modellers

Limitations

Constraints llm-inferred

Runs inside a licensed desktop Metashape Professional 2.3+ session; not a standalone data source · Viewport and screenshot tools are unavailable in headless mode · Direct HTTP connection from Claude Code times out after about 60 seconds; the stdio proxy is needed for long jobs and requires a separate FastMCP install · ENTRY tool names (aerial_survey_pipeline, close_range_pipeline, batch_export, diagnose_alignment, optimize_quality_settings) match the docs' guided workflow prompts, not documented callable tools · Tool argument schemas are not documented in the DOCS text · No credentials documented in README; the Metashape licence is separate from the MIT-licensed server

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

Zonal slope, aspect and elevation statistics over a site boundary from a DEM (geo-terrain dem_zonal) for drainage or civils options appraisal · Reproject and validate site boundary and survey vectors (geo-ops CRS transforms, geometry validation) before exchange with clients · Summer Sentinel-2 scene search over a site bbox (geo-stac) for pre-development land cover context · Species occurrence and OSM feature pulls (geo-biodiversity, geo-vector) as inputs to an ecological desk-study baseline

Audience llm-inferred

GIS analysts · geospatial developers · hydrologists · ecologists

Limitations

Constraints docs-verified

Foundation-model embeddings use a stand-in backend by default; real weights need a configured backend · Credentialed servers (geo-warehouse, geo-commercial-imagery, NOAA CDO, IUCN Red List) need API or cloud credentials · ERA5 is reached via the Open-Meteo archive, not a direct CDS client · Copernicus CLMS covers land-monitoring products, not raw Sentinel · Heavy compute depends on the separate aws-geo-compute peer Power and an AWS account · Without the [pdal] extra, point-cloud output is a local container and not interoperable COPC · Repository is named sample-*, so treat it as a reference implementation and assess maintenance risk

Useful for

Use cases llm-inferred

Desk-based site context overview (terrain, imagery, nearby live signals) before a site visit · Weather context review for an event window using forecast wind and observed radar replay · Visual briefing material for client and stakeholder presentations using scene capture

Audience llm-inferred

GIS analysts · flood consultants (visualisation only) · planners · civils/BIM engineers (visualisation only)

Limitations

Constraints llm-inferred

Traffic is simulated along real roads from aggregate location data, not measured · CCTV camera poses and rocket launch trajectories are coarse estimates · Public camera feeds only over listed regions · Google Maps and Cesium ion features are subject to provider terms and quotas · Voice control requires an OpenAI key · Bundled Nepal flood data is non-commercial only · Licence listed as Other, so reuse terms need checking before commercial use · Older versions no longer work with OpenStreetMap data sources and need updating

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

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

Batch-geocode up to 10 project addresses to coordinates for a site or consultee list · Elevation profile along a proposed drainage or pipe route for gradient screening · Buffer a site point or boundary by a set distance to define a consultation or search zone · Reproject layers between CRS (e.g. EPSG:4326 to EPSG:3857) before combining datasets

Audience llm-inferred

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

Limitations

Constraints llm-inferred

DOCS describe 'LocuSync Server' (repo matbel91765/locusync-server, PyPI locusync-server), not 'GIS-MCP-Server' as named in ENTRY; confirm the docs belong to this entry's repo before publishing · Default geocoding is Nominatim/OSM, enforced at 1 request/second; Pelias is only used when PELIAS_URL is set (default empty) · Default routing uses the OSRM demo server, which is best effort; self-hosting is advised for production · batch_geocode is capped at 10 addresses per request · DOCS do not state the elevation data source, resolution or vintage (Open-Elevation is the default endpoint) · DOCS do not state UK or regional coverage, or any time span · Valhalla native isochrones, PostGIS queries and full ESRI FileGDB support are roadmap items and not complete · Python 3.11+ required (per README badge)

Example tool calls docs-verified

{
  "tool": "distance",
  "arguments": {
    "lat1": 52.4862,
    "lon1": -1.8904,
    "lat2": 51.5074,
    "lon2": -0.1278
  }
}

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

As-built vs design QA: cloud-to-mesh distances between a laser scan of an earthwork or structure and its design surface · Survey clean-up before deliverables: statistical outlier removal and spatial subsampling of lidar or scan data · Multi-epoch change detection: cloud-to-cloud distances between repeat scans of a slope, bank or channel · Scan registration: ICP alignment of survey scans taken from different setups

Audience llm-inferred

BIM/civils engineers · geotechnical engineers · GIS analysts · surveyors

Limitations

Constraints llm-inferred

Most tools need a local CloudCompare ≥ 2.12 install; only read_cloud_metadata and visualize_cloud work without it · Requires Python ≥ 3.10 and uv or pip · run_cloudcompare_command is a raw CLI escape hatch and is not constrained by the server · SHP is listed as a supported file format but not among the convert_format targets · Single open-source GitHub project; maintenance and long-term support are unknown · Output quality depends on input cloud quality and CloudCompare's own behaviour, which the docs do not cover

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

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

Scripting buffer, clip and intersect geoprocessing on drainage or site boundary layers · Diagnosing CRS mismatches when combining BIM/IFC site models with GIS data · Generating print-ready site plan layouts and PDF exports for consultation documents · Computing hillshade, slope and aspect from DEMs for civils terrain review

Audience llm-inferred

GIS analysts · drainage engineers · hydrologists · BIM/civils engineers · QGIS plugin developers

Limitations

Constraints llm-inferred

Teaches Claude how to write PyQGIS code; it does not control a running QGIS instance (runtime control needs a separate MCP server) · Targets QGIS 3.44 LTR; QGIS 4.0 is covered only by compatibility notes · Not a data source: provides no UK datasets, gauges, DEMs or rainfall data · No UK-specific guidance (for example British National Grid) is documented · Install instructions point to the OpenAEC-Foundation repository, which differs from the listed URL (Impertio-Studio) · Requires a local Claude Code setup and a local QGIS installation to run the resulting code

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

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