OSM Analytics Server
FreeNot checkedProvides advanced geospatial analytics for OpenStreetMap, including neighborhood livability scoring and commute analysis, beyond simple geocoding.
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Provides advanced geospatial analytics for OpenStreetMap, including neighborhood livability scoring and commute analysis, beyond simple geocoding.
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 OSM Analytics Server
This server has no published package — it is built from source. Open the repository and follow its README.
▸ github.com/neco001/openstreetmap-mcpFAQ
Is OSM Analytics Server MCP free?
Yes, OSM Analytics Server MCP is free — one-click install via Unyly at no cost.
Does OSM Analytics Server need an API key?
No, OSM Analytics Server runs without API keys or environment variables.
Is OSM Analytics Server hosted or self-hosted?
A hosted option is available: Unyly runs the server in the cloud, no local setup required.
How do I install OSM Analytics Server in Claude Desktop, Claude Code or Cursor?
Open OSM Analytics Server 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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