OSM MCP Analytics Server
Provides geospatial analytics and tools including geocoding, routing, nearby place search, neighborhood livability scoring, and commute analysis using OpenStreetMap data.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@OSM MCP Analytics Serveranalyze neighborhood livability in downtown Seattle"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Enterprise OpenStreetMap (OSM) MCP Analytics Server
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.
š 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.
Related MCP server: chuk-mcp-geocoder
š Features
Core Tools
Geocoding:
geocode_address,reverse_geocodeRouting:
get_route_directions(OSRM based)Search:
find_nearby_places,search_categoryAnalytics:
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.
š¦ 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 syncš Project Structure
src/openstreetmap_mcp/
āāā server.py # Main Entry Point
āāā instance.py # FastMCP lifecycle
āāā client.py # HTTP logic for OSM/OSRM/Overpass
āāā utils.py # Haversine & geometric helpers
āāā tools/ # Categorized tool definitions
ā āāā geocoding.py
ā āāā routing.py
ā āāā search.py
ā āāā analysis.py
āāā resources.py # Map & Data resourcesāļø 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.
This server cannot be deployed
Maintenance
Related MCP Connectors
Geocode, reverse geocode, and run Overpass spatial queries on OpenStreetMap data.
Geocode, reverse geocode, and run Overpass spatial queries on OpenStreetMap data.
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