GIS MCP Server

GIS MCP Server

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

Alpha

Version 0.6.0 (Beta) is under active development. We welcome contributions and developers to join us in building this project.

🎥 Demo

Rasterio Demo

📋 Table of Contents

• Features
• Prerequisites
• Installation
  • Installing via Smithery
  • pip Installation
  • Development Installation
• Available Functions
  • Shapely Functions
  • PyProj Functions
  • GeoPandas Functions
  • Rasterio Functions
  • PySAL Functions
• Client Development
• Planned Features
• Contributing
• License
• Related Projects
• Support
• Badges

🚀 Features

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.

📋 Prerequisites

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

🛠 Installation

Choose the installation method that best suits your needs:

🛠 Installing via Smithery

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

📦 pip Installation

The pip installation is recommended for most users:

1. Install uv package manager:

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

3. Install the package:

4. Start the server:

pip Configuration

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

Claude Desktop:

Windows:

Linux/Mac:

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

Windows:

Linux/Mac:

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!

🛠 Development Installation

For contributors and developers:

1. Install uv package manager:

2. Create the Virtual Environment:

3. Install the package in development mode:

4. Start the server:

Development Configuration

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

Claude Desktop:

Windows:

Linux/Mac:

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

Windows:

Linux/Mac:

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!

📚 Available Functions

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

🔷 Shapely Functions (29 total)

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

🔷 PyProj Functions (11 total)

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

🔷 GeoPandas Functions (11 total)

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

🔷 Rasterio Functions (18 total)

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

🔷 PySAL Functions (15 total)

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

Total Functions Available: 84

🛠 Client Development

Example usage of the tools:

Buffer Operation

Coordinate Transformation

Geodetic Distance

🔮 Planned Features

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

🤝 Contributing

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.

📄 License

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

🔗 Related Projects

• Model Context Protocol - The core MCP implementation
• Shapely - Python package for manipulation and analysis of geometric objects
• PyProj - Python interface to PROJ library
• GeoPandas - Python package for working with geospatial data
• Rasterio - Python package for reading and writing geospatial raster data
• PySAL - PySAL, the Python spatial analysis library for geospatial data science with an emphasis on geospatial vector data written in Python.

📞 Support

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

💬 Community

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

👥 Contributors

Made with contrib.rocks.

🏆 Badges