Find your next source.

Useful for

Use cases llm-inferred

Build a FLAC3D slope model and estimate factor of safety · Model tunnel excavation in jointed rock with 3DEC and check block displacements · Simulate landslide runout with MPoint and report the final deposit profile · Check unbalanced force on a PFC simulation while it is still running

Audience llm-inferred

geotechnical engineers · geomechanics modellers · civils engineers · researchers using ITASCA software

Limitations

Constraints docs-verified

Requires an ITASCA engine installed locally · Execution tools require the bridge to be started inside the engine GUI or IPython console · Engine version support is limited to the listed versions (PFC 6.0/7.0/9.0, FLAC 7.0/9.0, 3DEC 7.0/9.0, with 9.0+ recommended) · Documentation tools work without the bridge

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

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

Useful for

Use cases llm-inferred

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

Audience llm-inferred

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

Limitations

Constraints docs-verified

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

Example tool calls docs-verified

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

Useful for

Use cases llm-inferred

Pre-issue model check before sheet issue (revit_pre_issue_check) · Model audit of a Revit project for QA (revit_model_audit) · Drawing and sheet layout automation for issue sets (revit_drawing_layout) · Stair modelling and checks (revit_stairs)

Audience llm-inferred

BIM coordinators · BIM/civils engineers · Revit modellers

Limitations

Constraints llm-inferred

Windows only: the installer and PowerShell setup target a Windows machine · Revit must be open with a model, and MCP must be started from the ribbon each session · Revit versions limited to 2022–2027 · Early implementation, researched and implemented since March 2026 · Family Editor authoring is out of scope · Local only: no remote access; connects to Revit via localhost TCP (≤2024) or a named pipe (≥2025)

Useful for

Use cases llm-inferred

Pre-issue QA: audit view and sheet naming conventions across a drainage or civils model · Schedule checks: pull schedule rows and compare schedules for quantity reconciliation · Parameter QA: read element properties and flag missing values before exporting data · Visual review: export a view image of a drainage run or structure for markup in a design review

Audience llm-inferred

BIM/civils engineers · BIM managers and coordinators · drainage engineers · BIM/CAD technicians

Limitations

Constraints llm-inferred

Needs a live Revit session with a project open; no offline or file-based access · Requires pyRevit and the Revit Routes server enabled · Web UI binds to 127.0.0.1 by default; LAN sharing is for trusted networks only · Claude Desktop local MCP runs on one machine only · Schedule formula text is unsupported (public Revit 2024 API only) · Install instructions are Windows-specific · Tool argument schemas are not documented in DOCS

Useful for

Use cases llm-inferred

Model QA before design coordination: list Revit warnings and the affected element IDs · Parameter corrections on drainage or structural elements, applied only after human-approved plans · Read-only IFC storey and property checks on consultant models without opening Revit

Audience llm-inferred

BIM coordinators · BIM managers · BIM/civils engineers

Limitations

Constraints docs-verified

Pre-release: nothing has been verified in a live Revit session yet · Describes the dev branch; the latest GitHub release may not include all features · Live Revit work limited to Windows and Revit 2024 to 2027 · Approving a plan changes the open model; test on a copy first · Snapshot QA/QC and report modules need snapshot_id; model_bloat lacks the guard · Advanced tools (revit_execute_python, revit_invoke_method) have the full permissions of the Revit process · Navisworks support is in progress · No UK-specific standards, datasets or civils tooling described in the docs

Useful for

Use cases llm-inferred

Stormwater drainage model build from GIS inputs with QA and audit trail · Peak-flow and rainfall-runoff screening for drainage strategy options · Reproducible SWMM run handover with provenance records for client review

Audience llm-inferred

drainage engineers · hydrologists · stormwater modellers · GIS analysts

Limitations

Constraints llm-inferred

Pre-1.0 (v0.9.4), so interfaces may change · Real storm networks only for 35 Canadian cities via SWMMCanada; elsewhere SWMManywhere synthesis, which is not a calibrated or validated network · Validation rows are evidence-bounded: GIS preprocessing concept, prepared-input path and uncertainty smoke are not calibrated performance claims · Raw GIS path handles structured layers only, not arbitrary CAD/GIS recognition · ENTRY lists region as United States, but DOCS do not describe US or UK coverage, so UK suitability is unverified · Agent features need an LLM provider; one-line installers run a remote script · ENTRY auth says no credentials documented, but DOCS describe API key configuration · No MCP tool names or transport documented in DOCS; ENTRY tools list is empty · One evidence row (v0.7.1) states calibration is next-milestone scope

Useful for

Use cases llm-inferred

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

Audience llm-inferred

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

Limitations

Constraints docs-verified

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

Useful for

Use cases llm-inferred

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

Audience llm-inferred

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

Limitations

Constraints docs-verified

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

Useful for

Use cases llm-inferred

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

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

Audience llm-inferred

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

Limitations

Constraints llm-inferred

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

Useful for

Use cases llm-inferred

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

Audience llm-inferred

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

Limitations

Constraints llm-inferred

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

Useful for

Use cases llm-inferred

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

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

Country-level socio-economic baseline indicators (GDP, poverty) for international ESIA or socio-economic chapters · Climate-related indicator context for overseas water or civils options appraisal · Agent-assisted indicator search with country coverage check before drafting a report · Retrieve indicator time series with metadata for methodology notes in technical appendices

Audience llm-inferred

AI and chatbot developers building agents on World Bank data · environmental consultants (socio-economic baselines, ESIA) · water and civils consultants working on international projects · GIS analysts

Limitations

Constraints llm-inferred

Indicator data only; no UK-specific, gauge-level or site-scale data indicated · No spatial or temporal resolution or update cadence documented · Requires a local Python install and MCP client; default endpoint is localhost · Depends on upstream Data360 API availability; stale metadata may be reused during degradation · Licence field is 'Other' (MIT plus IGO Rider); review before redistribution · Documented API calls are read-only retrievals; no write or analysis tools listed

Useful for

Use cases llm-inferred

Serve a client's GeoParquet or PMTiles dataset from its existing bucket as an OGC API, without loading it into a database · Expose project geodata to QGIS or partner systems via OGC API Features with OIDC-protected access · Give AI agents read access to project geospatial collections through the MCP endpoint

Audience llm-inferred

GIS analysts · GIS developers · data engineers · geospatial platform administrators

Limitations

Constraints llm-inferred

Cloud Optimized GeoTIFF has no native provider; only a worked example is documented · Requires Python 3.12 or later · Enterprise identity (EMA/ID-JAG) is noted as still under verification · Tracks pygeoapi releases, so upstream changes feed into maintenance · MCP tool list is empty in ENTRY metadata

Useful for

Use cases llm-inferred

Swiss station rainfall and temperature series for a project-site climate baseline · Radar precipitation composites for storm event reconstruction in Swiss catchments · NetCDF climate scenario grids for future rainfall sensitivity checks on Swiss projects · GRIB2 forecast fields for short-term weather context on Swiss site works

Audience llm-inferred

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

Limitations

Constraints llm-inferred

Covers MeteoSwiss (Switzerland) data only; no UK coverage · Requires Python 3.11 or later · Gridded data (xarray/Zarr) needs the optional grids extra · Spark/Databricks ingestion is optional and not needed for local use · MCP tool names are not listed in the provided docs · Source data update frequency is not stated

Useful for

Use cases llm-inferred

Log project decisions and meeting notes, linked by backlinks, for a consultancy project · Keep research trails for a site investigation or desk study connected as the thinking develops · Track ideas and open actions with reminders and saved table views across a project

Audience llm-inferred

project managers · consultants · researchers · project teams

Limitations

Constraints llm-inferred

Not an environmental, hydrological or geospatial data source; the docs describe a note-taking workspace · Persistent, shared use requires self-hosting; the live demo has no server-backed features · Source development requires Node.js 22.13+ and pnpm 10.25.0 · Access beyond the user's own machine requires password mode

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

Portal content inventory and stale-content governance audit before handover of a project GIS deliverable · Broken-reference and service health check on web maps and layers before issuing them to field or client teams · Export of project web map layers as PNG/PDF for consultancy report figures · Attribute query of hosted feature layers (e.g. asset or site records) for data QA

Audience llm-inferred

GIS analysts · GIS and portal administrators · environmental and civils consultancy staff who manage ArcGIS Online or Enterprise content

Limitations

Constraints llm-inferred

Independent open-source project, not affiliated with Esri (per DOCS disclaimer) · Requires portal credentials; catalogue auth field conflicts with DOCS · Many tools are write or destructive (delete, share, offboard_user, batch operations); read-only mode via MCP_READ_ONLY=true should be set for exploratory use · Admin tools such as portal_health require administrator privileges · Publishing behaviour is version-specific (fixes for ArcGIS Enterprise 12.x in v1.14.0) · Self-signed Enterprise certificates need MCP_TLS_VERIFY=false, which weakens TLS verification

Useful for

Use cases llm-inferred

Tender technical-bid compliance matrix, missing-document list and bid-risk flags from tender files (aios-tender-audit) · Special construction scheme review: hazard list, disclosure points and calculation-sheet gaps (aios-scheme-audit) · Building a norm-excerpt Knowledge Pack with citations for internal lookup (aios-knowledge)

Audience llm-inferred

construction tender and technical-bid staff · project document controllers · technical leads for construction schemes · AI/software teams building construction tools

Limitations

Constraints docs-verified

Knowledge Pack is not a production-grade norms database · Does not replace legal, chief engineer, expert, review or registered-professional sign-off · Docs describe Chinese-language construction workflows; no UK standards, water or civils coverage is documented · Not intended for non-construction tasks; outputs need human review

Useful for

Use cases llm-inferred

Preflight-checked inspection and summary of existing DWG drawings before civils or drainage design review · Guarded, dry-run-verified layer, annotation and dimension clean-up of CAD deliverables before issue · Generating PDF plot and PNG visual evidence of drainage or civils layouts for internal QA

Audience llm-inferred

civils engineers · drainage engineers · BIM and CAD technicians · GIS and CAD analysts

Limitations

Constraints docs-verified

Beta software, intended for controlled local use with operator review rather than unattended changes to production drawings · Windows only; requires AutoCAD running as the same Windows user · Not claimed to comply with formal ISO, GB or ASME standards · Requires a local MCP client; no hosted or remote operation

Useful for

Use cases llm-inferred

Discover NASA Earthdata datasets for a study area using keyword and bounding-box search · Preview granule scope for a time window in manifest mode before committing to a bulk download · Generate notebook-ready download scripts for satellite data analysis in script mode · Pull granules into a project folder on a server runtime in download mode where server-side writes are intended

Audience llm-inferred

hydrologists · GIS analysts · flood consultants · environmental consultants · civils and water engineers working with satellite data

Limitations

Constraints docs-verified

Download mode requires NASA Earthdata Login credentials · Download mode writes files to the server runtime, not the user's machine · Earthdata-only: no notebook or runtime tools in the server itself · Coverage area, time span and resolution are not stated in the 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

Swiss river baseline screening: nearby BAFU hydro stations and current water levels/temperature for a site (get_water_level, list_hydro_stations) · Swiss weather inputs for a project: MeteoSwiss station list and historical weather for a site period (list_weather_stations, get_weather_history) · Swiss site constraints screening: dam registry lookup by canton for a Swiss site (get_dams_by_canton) · Swiss air quality baseline: NABEL station data and LRV limits near a site (list_air_quality_stations, get_air_quality)

Audience llm-inferred

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

Limitations

Constraints llm-inferred

Covers Switzerland only; no UK data, so not relevant to UK sites · Historical weather data is limited to a window of up to 32 days per request · Data is served from third-party Swiss agencies (BAFU, MeteoSwiss, swisstopo, etc.), so availability depends on those sources · Runs as a community npm/Docker package; maintenance risk sits with a single upstream repository · Loads 79 tools by default, which costs tokens; module filtering is needed for efficiency

Useful for

Use cases llm-inferred

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

Audience llm-inferred

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

Limitations

Constraints llm-inferred

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