matbel91765/gis-mcp-server
by Various
๐ ๐ ๐ ๐ช ๐ง - Geospatial tools for AI agents: geocoding, routing, elevation, spatial analysis, and file I/O (Shapefile, GeoJSON, GeoPackage)
MCP
matbel91765/gis-mcp-server
Added 1 June 2026
Overview
An open-source MCP server providing geospatial tools for AI agents. It supports geocoding, routing, elevation queries, spatial analysis, and file I/O for Shapefile, GeoJSON, and GeoPackage formats. Built in Python, it integrates with AI agent workflows via the Model Context Protocol.
Best for
Best for
Developers building AI agents that need basic geospatial analysis and file handling capabilities
Use cases
- Geocode addresses for location enrichment in agent responses
- Calculate routes or elevation profiles for spatial reasoning tasks
- Read and write geospatial files to process GIS data
Notes
An open-source MCP server providing geospatial tools for AI agents. It supports geocoding, routing, elevation queries, spatial analysis, and file I/O for Shapefile, GeoJSON, and GeoPackage formats. Built in Python, it integrates with AI agent workflows via the Model Context Protocol.
3 stars on GitHub. Last updated 2025-12-05. Licensed MIT.
Use cases
- Geocode addresses for location enrichment in agent responses
- Calculate routes or elevation profiles for spatial reasoning tasks
- Read and write geospatial files to process GIS data
Pros
- Offers a wide range of geospatial operations in a single server
- Uses standard MCP protocol for easy integration with AI agents
- Open source with permissive licensing, allowing customization
Cons
- Low community adoption (3 stars) suggests limited testing and support
- Python-only dependency may restrict deployment environments
- Documentation and examples are minimal, requiring self-guided setup
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Offers a wide range of geospatial operations in a single server
- Uses standard MCP protocol for easy integration with AI agents
- Open source with permissive licensing, allowing customization
Cons
- Low community adoption (3 stars) suggests limited testing and support
- Python-only dependency may restrict deployment environments
- Documentation and examples are minimal, requiring self-guided setup
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.