open-streetmap-mcp and osmmcp
These two OpenStreetMap MCP server implementations are competitors, offering similar geospatial tools and location-based services for enhancing LLM capabilities.
About open-streetmap-mcp
jagan-shanmugam/open-streetmap-mcp
An OpenStreetMap MCP server implementation that enhances LLM capabilities with location-based services and geospatial data.
Implements 12+ geospatial tools including geocoding, routing, POI discovery, and neighborhood analysis through a stdio-based MCP server compatible with Claude Desktop, Cursor, and Windsurf. Built on OpenStreetMap data with resources for place lookups and styled map tiles, enabling LLMs to power location-aware applications like meeting point optimization, commute analysis, and real estate evaluation. Uses Python with the MCP framework and includes example clients demonstrating both basic tool invocation and LLM integration patterns.
About osmmcp
NERVsystems/osmmcp
OpenStreetMap MCP server providing precision geospatial tools for LLMs via Model Context Protocol. Features geocoding, routing, nearby places, neighborhood analysis, EV charging stations, and more.
Built in Go with the mcp-go library, it uses stdio transport and implements 24+ composable geospatial tools—including polyline encoding/decoding, OSRM routing integration, and emissions enrichment—designed as functional primitives where tool outputs chain seamlessly as inputs to enable emergent LLM workflows. Beyond standard geocoding, it provides specialized analyzers for neighborhood livability, EV charging along routes, commute comparison across transport modes, and school/parking discovery, with uniform interfaces and precise error handling for reliable MCP client integration.
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