Openstreetmap
FreeNot checkedAdvanced OpenStreetMap MCP Server for AI Agents. Goes beyond geocoding with Neighborhood Livability Scoring and Commute Analysis. Modular, stable, and Windows-r
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Advanced OpenStreetMap MCP Server for AI Agents. Goes beyond geocoding with Neighborhood Livability Scoring and Commute Analysis. Modular, stable, and Windows-ready.
README
A modular, high-performance Model Context Protocol (MCP) server for OpenStreetMap. This implementation goes beyond simple geocoding, providing advanced geospatial analytics like neighborhood livability scoring and commute analysis.
🚀 Why this server?
While there are many OSM MCP servers, this version is built for stability, modular extension, and advanced insights:
- Modular Architecture: Clean separation between API Client, Utility logic, and Tool definitions. Easy to audit and extend.
- Enterprise Analytics:
analyze_neighborhood: Calculates a "Livability Score" based on walking proximity to essential services (groceries, healthcare, parks).analyze_commute: Multi-modal comparison of travel times (car, bike, foot) for lifestyle planning.
- Efficient: Uses FastMCP for asynchronous I/O and structured tool registration.
- Windows Optimized: Built and tested to run reliably as a background process on Windows environments.
🛠 Features
Core Tools
- Geocoding:
geocode_address,reverse_geocode - Routing:
get_route_directions(OSRM based) - Search:
find_nearby_places,search_category - Analytics:
explore_area,analyze_neighborhood,analyze_commute
Specialized Tools (Optional)
Found in tools/extras.py (not loaded by default for performance):
find_schools_nearbyfind_ev_charging_stationsfind_parking_facilitiessuggest_meeting_point
Resources
location://place/{query}: Real-time place metadata.location://map/{style}/{z}/{x}/{y}: Interactive map tile retrieval.
📦 Installation
Requirements
- Python 3.10+
uv(recommended) orpip
Method 1: Via MCP Config (Claude/Cursor)
Add this to your mcp_config.json:
{
"mcpServers": {
"osm-mcp": {
"command": "python",
"args": [
"c:/path/to/osm-mcp-server/src/openstreetmap_mcp/server.py"
],
"env": {
"PYTHONPATH": "c:/path/to/osm-mcp-server/src/openstreetmap_mcp"
}
}
}
}
Method 2: Local Development
git clone https://github.com/neco001/openstreetmap-mcp
cd openstreetmap-mcp
uv sync
📂 Project Structure
src/openstreetmap_mcp/
├── server.py # Main Entry Point
├── instance.py # FastMCP lifecycle
├── client.py # HTTP logic for OSM/OSRM/Overpass
├── utils.py # Haversine & geometric helpers
├── tools/ # Categorized tool definitions
│ ├── geocoding.py
│ ├── routing.py
│ ├── search.py
│ └── analysis.py
└── resources.py # Map & Data resources
⚖️ License
MIT License - feel free to use, modify and distribute.
Acknowledgments
Original logic & concepts by Jagan Shanmugam. This repository is a modular refactor focused on Enterprise usage, Windows compatibility, and Analytics tools.
Installing Openstreetmap
This server has no published package — it is built from source. Open the repository and follow its README.
▸ github.com/neco001/openstreetmap-mcpFAQ
Is Openstreetmap MCP free?
Yes, Openstreetmap MCP is free — one-click install via Unyly at no cost.
Does Openstreetmap need an API key?
No, Openstreetmap runs without API keys or environment variables.
Is Openstreetmap hosted or self-hosted?
Self-hosted: the server runs locally on your machine via the install command above.
How do I install Openstreetmap in Claude Desktop, Claude Code or Cursor?
Open Openstreetmap on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.
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