Give Your LLM Real Geographic Intelligence

Stop 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.

The Location Data Problem Every Developer Faces

You're building location-aware applications, but hitting the same walls:

• Google Maps API costs spiral out of control for anything beyond basic geocoding
• LLMs give vague, hallucinated responses about specific locations
• You need 3-4 different services just to handle geocoding, routing, and place search
• Building a "find the best meeting spot for 5 people" feature requires complex spatial calculations

Why This Changes Everything

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.

What You Get Out of the Box

Advanced Spatial Intelligence:

• suggest_meeting_point - Finds optimal locations based on multiple people's positions and preferences
• analyze_neighborhood - Real estate-grade livability analysis with walkability scores
• analyze_commute - Multi-modal transportation analysis between any two points

Complete Location Stack:

• Bidirectional geocoding (address ↔ coordinates)
• Multi-modal routing (driving, walking, cycling)
• Category-based place search with radius filtering
• EV charging station finder with connector type and power filtering
• School district and educational facility mapping

Production-Ready Features:

• Comprehensive error handling and rate limiting
• Built-in progress tracking for complex queries
• Map tile generation for visual confirmation
• Full MCP compliance for seamless integration

Use Cases That Actually Matter

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.

Integration is Actually Simple

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.

Why Developers Are Switching

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.