GIS MCP Server

A Model Context Protocol (MCP) server providing geospatial tools for AI agents. Enables Claude, GPT, and other LLMs to perform geocoding, routing, spatial analysis, and file operations.

Features

• Geocoding: Convert addresses to coordinates and vice versa (via Nominatim/OSM or Pelias)
• Batch Geocoding: Geocode multiple addresses in a single request (up to 10)
• Elevation Data: Get altitude for points and elevation profiles along paths
• Routing: Calculate routes between points with distance, duration, and geometry (via OSRM)
• Spatial Analysis: Buffer, intersection, union, distance calculations
• File I/O: Read/write Shapefiles, GeoJSON, GeoPackage
• CRS Transformation: Convert between coordinate reference systems

Installation

# From PyPI (when published)
pip install gis-mcp-server

# From source
git clone https://github.com/matbel91765/gis-mcp-server.git
cd gis-mcp-server
pip install -e .

Quick Start

With Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "gis": {
      "command": "uvx",
      "args": ["gis-mcp-server"]
    }
  }
}

Direct Usage

# Run the server
gis-mcp-server

Available Tools

Geocoding

geocode

Convert an address to coordinates.

Input: "1600 Pennsylvania Avenue, Washington DC"
Output: {lat: 38.8977, lon: -77.0365, display_name: "White House..."}

reverse_geocode

Convert coordinates to an address.

Input: lat=48.8566, lon=2.3522
Output: {display_name: "Paris, Île-de-France, France", ...}

batch_geocode

Geocode multiple addresses at once (max 10).

Input: addresses=["Paris, France", "London, UK", "Berlin, Germany"]
Output: {results: [...], summary: {total: 3, successful: 3, failed: 0}}

Elevation

get_elevation

Get altitude for a point.

Input: lat=48.8566, lon=2.3522
Output: {elevation_m: 35, location: {lat: 48.8566, lon: 2.3522}}

get_elevation_profile

Get elevations along a path.

Input: coordinates=[[2.3522, 48.8566], [2.2945, 48.8584]]
Output: {profile: [...], stats: {min: 28, max: 42, gain: 14}}

Geometry

distance

Calculate distance between two points.

Input: lat1=48.8566, lon1=2.3522, lat2=51.5074, lon2=-0.1278
Output: {distance: {meters: 343556, kilometers: 343.56, miles: 213.47}}

buffer

Create a buffer zone around a geometry.

Input: geometry={type: "Point", coordinates: [2.3522, 48.8566]}, distance_meters=1000
Output: {geometry: {type: "Polygon", ...}, area_km2: 3.14}

spatial_query

Perform spatial operations (intersection, union, contains, within, etc.).

Input: geometry1={...}, geometry2={...}, operation="intersection"
Output: {geometry: {...}}

transform_crs

Transform coordinates between CRS.

Input: geometry={...}, source_crs="EPSG:4326", target_crs="EPSG:3857"
Output: {geometry: {...}}

Routing

route

Calculate route between two points.

Input: start_lat=48.8566, start_lon=2.3522, end_lat=48.8606, end_lon=2.3376
Output: {distance: {...}, duration: {...}, geometry: {...}, steps: [...]}

isochrone

Calculate area reachable within a time limit.

Input: lat=48.8566, lon=2.3522, time_minutes=15, profile="driving"
Output: {geometry: {type: "Polygon", ...}}

Files

read_file

Read geospatial files (Shapefile, GeoJSON, GeoPackage).

Input: file_path="data/cities.shp"
Output: {type: "FeatureCollection", features: [...]}

write_file

Write features to geospatial files.

Input: features={...}, file_path="output.geojson", driver="GeoJSON"
Output: {file_path: "...", feature_count: 10}

Configuration

Environment variables:

Response Format

All tools return a consistent JSON structure:

{
  "success": true,
  "data": { ... },
  "metadata": {
    "source": "nominatim",
    "confidence": 0.95
  },
  "error": null
}

Rate Limits

• Nominatim: 1 request/second (enforced automatically)
• OSRM Demo: Best effort, consider self-hosting for production

Development

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest

# Run with coverage
pytest --cov=src/gis_mcp --cov-report=html

# Type checking
mypy src/gis_mcp

# Linting
ruff check src/gis_mcp

Architecture

src/gis_mcp/
├── server.py      # MCP server entry point
├── config.py      # Configuration management
├── utils.py       # Common utilities
└── tools/
    ├── geocoding.py   # geocode, reverse_geocode, batch_geocode
    ├── elevation.py   # get_elevation, get_elevation_profile
    ├── routing.py     # route, isochrone
    ├── geometry.py    # buffer, distance, spatial_query, transform_crs
    └── files.py       # read_file, write_file

License

MIT License - see LICENSE for details.

Contributing

Contributions welcome! Please read the contributing guidelines before submitting PRs.

Roadmap

• Pelias geocoding support (higher accuracy)
• Elevation/terrain data
• Batch geocoding
• Valhalla routing integration (native isochrones)
• PostGIS spatial queries
• Real-time traffic data
• ESRI FileGDB full support