An OpenStreetMap MCP server implementation that enhances LLM capabilities with location-based services and geospatial data.
https://github.com/jagan-shanmugam/open-streetmap-mcpStop wrestling with expensive mapping APIs and incomplete location data. This OpenStreetMap MCP server turns any LLM into a geospatial powerhouse that actually understands places, routes, and spatial relationships.
You're building location-aware applications, but hitting the same walls:
This MCP server plugs directly into OpenStreetMap's rich dataset, giving your LLM 12 specialized geospatial tools that work together intelligently. No API keys, no rate limits, no vendor lock-in.
Real-world capability: Ask "Find a coffee shop equidistant from these three offices where my team can meet" and get actual coordinates with walking directions, not generic suggestions.
Advanced Spatial Intelligence:
suggest_meeting_point - Finds optimal locations based on multiple people's positions and preferencesanalyze_neighborhood - Real estate-grade livability analysis with walkability scoresanalyze_commute - Multi-modal transportation analysis between any two pointsComplete Location Stack:
Production-Ready Features:
Meeting Coordination: Your LLM can solve "Where should we meet?" by analyzing everyone's location, preferred transportation, and venue requirements - then provide walking directions to each person.
Real Estate Intelligence: Get instant neighborhood analysis including walkability, nearby amenities, school ratings, and commute times to major employment centers.
Urban Planning Queries: "Show me all the coffee shops within 10 minutes of these subway stops" becomes a single conversation, not a research project.
EV Trip Planning: Find charging stations along routes with specific connector types and minimum power ratings, automatically factoring in charging time.
Add to Claude Desktop in 30 seconds:
"mcpServers": {
"osm-mcp-server": {
"command": "uvx",
"args": ["osm-mcp-server"]
}
}
The server runs locally, connects to OpenStreetMap's public APIs, and requires zero configuration. Your LLM immediately gains geographic reasoning capabilities.
Unlike traditional mapping APIs that charge per request and limit functionality, this gives you unrestricted access to the same data that powers major mapping applications. The MCP architecture means your LLM can chain multiple geospatial operations intelligently - like finding a restaurant, checking its hours, getting directions, and finding nearby parking in a single conversation flow.
The 12 specialized tools work together seamlessly. Ask complex spatial questions and get precise, actionable answers instead of "I can help you find information about that."
This isn't just another mapping integration - it's geographic intelligence that makes your LLM genuinely useful for location-based problem solving.