GIS MCP Server

✨ Want to perform accurate geospatial analysis in your chatbot? ✨

Install GIS-MCP and transform your AI's spatial capabilities!

A Model Context Protocol (MCP) server implementation that connects Large Language Models (LLMs) to GIS operations using GIS libraries, enabling AI assistants to perform geospatial operations and transformations.

🌐 Website: gis-mcp.com

Current version is 0.8.0

Version 0.9.0 (Beta) is under active development. We welcome contributions and developers to join us in building this project.

• Features
• Prerequisites
• Installation
  • Installing via Smithery
  • pip Installation
  • Development Installation
• Available Functions
  • Shapely Functions
  • PyProj Functions
  • GeoPandas Functions
  • Rasterio Functions
  • PySAL Functions
  • Administrative Boundaries Functions
  • Climate Data Functions
  • Ecology Data Functions
  • Movement Data Functions
  • Land Cover Data Functions
  • Satellite Imagery Functions
• Client Development
• Planned Features
• Contributing
• License
• Related Projects
• Support
• Badges

GIS MCP Server empowers AI assistants with advanced geospatial intelligence. Key features include:

• 🔹 Comprehensive Geometry Operations – Perform intersection, union, buffer, difference, and other geometric transformations with ease.
• 🔹 Advanced Coordinate Transformations – Effortlessly reproject and transform geometries between coordinate reference systems.
• 🔹 Accurate Measurements – Compute distances, areas, lengths, and centroids precisely.
• 🔹 Spatial Analysis & Validation – Validate geometries, run proximity checks, and perform spatial overlays or joins.
• 🔹 Raster & Vector Support – Process raster layers, compute indices like NDVI, clip, resample, and merge with vector data.
• 🔹 Spatial Statistics & Modeling – Leverage PySAL for spatial autocorrelation, clustering, and neighborhood analysis.
• 🔹 Easy Integration – Connect seamlessly with MCP-compatible clients like Claude Desktop or Cursor IDE.
• 🔹 Flexible & Extensible – Supports Python-based GIS libraries and is ready for custom tools or workflow extensions.

🌟 Tip: With GIS MCP Server, your AI can now “think spatially,” unlocking new capabilities for environmental analysis, mapping, and location intelligence.

• Python 3.10 or higher
• MCP-compatible client (like Claude Desktop or Cursor)
• Internet connection for package installation

Choose the installation method that best suits your needs:

To install GIS MCP Server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @mahdin75/gis-mcp --client claude

The pip installation is recommended for most users:

1. Install uv package manager:

pip install uv

2. Create the Virtual Environment (Python 3.10+):

uv venv --python=3.10

3. Install the package:

uv pip install gis-mcp

4. Start the server:

gis-mcp

To use the pip installation with Claude or Cursor, add the following configuration:

Claude Desktop:

Windows:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "C:\\Users\\YourUsername\\.venv\\Scripts\\gis-mcp",
      "args": []
    }
  }
}

Linux/Mac:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "/home/YourUsername/.venv/bin/gis-mcp",
      "args": []
    }
  }
}

Cursor IDE (create .cursor/mcp.json):

Windows:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "C:\\Users\\YourUsername\\.venv\\Scripts\\gis-mcp",
      "args": []
    }
  }
}

Linux/Mac:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "/home/YourUsername/.venv/bin/gis-mcp",
      "args": []
    }
  }
}

After configuration:

1. Make sure to replace YourUsername with your actual username
2. For development installation, replace /path/to/gis-mcp with the actual path to your project
3. Restart your IDE to apply the changes
4. You can now use all GIS operations through Claude or Cursor!

For contributors and developers:

1. Install uv package manager:

pip install uv

2. Create the Virtual Environment:

uv venv --python=3.10

3. Install the package in development mode:

uv pip install -e .

4. Start the server:

python -m gis_mcp

To use the development installation with Claude or Cursor, add the following configuration:

Claude Desktop:

Windows:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "C:\\path\\to\\gis-mcp\\.venv\\Scripts\\python",
      "args": ["-m", "gis_mcp"]
    }
  }
}

Linux/Mac:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "/path/to/gis-mcp/.venv/bin/python",
      "args": ["-m", "gis_mcp"]
    }
  }
}

Cursor IDE (create .cursor/mcp.json):

Windows:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "C:\\path\\to\\gis-mcp\\.venv\\Scripts\\python",
      "args": ["-m", "gis_mcp"]
    }
  }
}

Linux/Mac:

{
  "mcpServers": {
    "gis-mcp": {
      "command": "/path/to/gis-mcp/.venv/bin/python",
      "args": ["-m", "gis_mcp"]
    }
  }
}

After configuration:

1. Make sure to replace YourUsername with your actual username
2. For development installation, replace /path/to/gis-mcp with the actual path to your project
3. Restart your IDE to apply the changes
4. You can now use all GIS operations through Claude or Cursor!

This section provides a comprehensive list of all available functions organized by library.

Basic Geometric Operations:

• buffer - Create buffer around geometry
• intersection - Find intersection of two geometries
• union - Combine two geometries
• difference - Find difference between geometries
• symmetric_difference - Find symmetric difference

Geometric Properties:

• convex_hull - Calculate convex hull
• envelope - Get bounding box
• minimum_rotated_rectangle - Get minimum rotated rectangle
• get_centroid - Get centroid point
• get_bounds - Get geometry bounds
• get_coordinates - Extract coordinate array
• get_geometry_type - Get geometry type name

Transformations:

• rotate_geometry - Rotate geometry by angle
• scale_geometry - Scale geometry by factors
• translate_geometry - Move geometry by offset

Advanced Operations:

• triangulate_geometry - Create triangulation
• voronoi - Create Voronoi diagram
• unary_union_geometries - Union multiple geometries

Measurements:

• get_length - Calculate geometry length
• get_area - Calculate geometry area

Validation & Utilities:

• is_valid - Check geometry validity
• make_valid - Fix invalid geometry
• simplify - Simplify geometry
• snap_geometry - Snap to reference geometry
• nearest_point_on_geometry - Find nearest point
• normalize_geometry - Normalize orientation
• geometry_to_geojson - Convert to GeoJSON
• geojson_to_geometry - Convert from GeoJSON

Coordinate Transformations:

• transform_coordinates - Transform point coordinates
• project_geometry - Project geometry between CRS

CRS Information:

• get_crs_info - Get detailed CRS information
• get_available_crs - List available CRS systems
• get_utm_zone - Get UTM zone for coordinates
• get_utm_crs - Get UTM CRS for coordinates
• get_geocentric_crs - Get geocentric CRS

Geodetic Calculations:

• get_geod_info - Get ellipsoid information
• calculate_geodetic_distance - Calculate distance on ellipsoid
• calculate_geodetic_point - Calculate point at distance/azimuth
• calculate_geodetic_area - Calculate area on ellipsoid

I/O Operations:

• read_file_gpd - Read geospatial file with preview
• write_file_gpd - Export GeoDataFrame to file

Join & Merge Operations:

• append_gpd - Concatenate GeoDataFrames vertically
• merge_gpd - Database-style attribute joins
• overlay_gpd - Spatial overlay operations
• dissolve_gpd - Dissolve by attribute
• explode_gpd - Split multi-part geometries

Spatial Operations:

• clip_vector - Clip geometries
• sjoin_gpd - Spatial joins
• sjoin_nearest_gpd - Nearest neighbor spatial joins
• point_in_polygon - Point-in-polygon tests

Basic Raster Operations:

• metadata_raster - Get raster metadata
• get_raster_crs - Get raster CRS
• extract_band - Extract single band
• raster_band_statistics - Calculate band statistics
• raster_histogram - Compute pixel histograms

Raster Processing:

• clip_raster_with_shapefile - Clip raster with polygons
• resample_raster - Resample by scale factor
• reproject_raster - Reproject to new CRS
• tile_raster - Split into tiles

Raster Analysis:

• compute_ndvi - Calculate vegetation index
• raster_algebra - Mathematical operations on bands
• concat_bands - Combine single-band rasters
• weighted_band_sum - Weighted band combination

Advanced Analysis:

• zonal_statistics - Statistics within polygons
• reclassify_raster - Reclassify pixel values
• focal_statistics - Moving window statistics
• hillshade - Generate hillshade from DEM
• write_raster - Write array to raster file

Spatial Autocorrelation:

• morans_i - Global Moran's I statistic
• gearys_c - Global Geary's C statistic
• gamma_statistic - Gamma index
• getis_ord_g - Global Getis-Ord G statistic

Local Statistics:

• moran_local - Local Moran's I
• getis_ord_g_local - Local Getis-Ord G*
• join_counts_local - Local join counts

Global Statistics:

• join_counts - Binary join counts test
• adbscan - Adaptive density-based clustering

Spatial Weights:

• weights_from_shapefile - Create weights from shapefile
• distance_band_weights - Distance-based weights
• knn_weights - K-nearest neighbors weights
• build_transform_and_save_weights - Build, transform, and save weights
• ols_with_spatial_diagnostics_safe - OLS regression with spatial diagnostics
• build_and_transform_weights - Build and transform weights

Boundary Download:

• download_boundaries - Download GADM administrative boundaries and save as GeoJSON

Climate Data Download:

• download_climate_data - Download climate data (ERA5 or other CDS datasets)

Ecology Data Download and Info:

• get_species_info – Retrieve taxonomic information for a given species name
• download_species_occurrences – Download occurrence records for a given species and save as JSON

Movement Data Download and Routing (via OSMnx):

• download_street_network – Download a street network for a given place and save as GraphML
• calculate_shortest_path – Calculate the shortest path between two points using a saved street network

Land Cover from Planetary Computer:

• download_worldcover – Download ESA WorldCover for AOI/year; optional crop and reprojection
• compute_s2_ndvi – Compute NDVI from Sentinel-2 L2A; crop and reprojection supported

STAC-based Satellite Download:

• download_satellite_imagery – Download and stack bands from STAC items (e.g., Sentinel-2, Landsat), with optional crop and reprojection

Total Functions Available: 89

Example usage of the tools:

Tool: buffer
Parameters: {
    "geometry": "POINT(0 0)",
    "distance": 10,
    "resolution": 16,
    "join_style": 1,
    "mitre_limit": 5.0,
    "single_sided": false
}

Tool: transform_coordinates
Parameters: {
    "coordinates": [0, 0],
    "source_crs": "EPSG:4326",
    "target_crs": "EPSG:3857"
}

Tool: calculate_geodetic_distance
Parameters: {
    "point1": [0, 0],
    "point2": [10, 10],
    "ellps": "WGS84"
}

• Implement advanced spatial indexing
• Implement network analysis capabilities
• Add support for 3D geometries
• Implement performance optimizations
• Add support for more GIS libraries

We welcome contributions! Here's how you can help:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Please ensure your PR description clearly describes the problem and solution. Include the relevant issue number if applicable.

This project is licensed under the MIT License - see the LICENSE file for details.

For support, please open an issue in the GitHub repository.

Join our Discord community for discussions, updates, and support:

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