OpenStreetMap (OSM) MCP Server

An OpenStreetMap MCP server implementation that enhances LLM capabilities with location-based services and geospatial data.

Demo

Meeting Point Optimization

Neighborhood Analysis

Parking Search

Installation

In MCP Hosts like Claude Desktop, Cursor, Windsurf, etc.

• osm-mcp-server: The main server, available for public use.

  "mcpServers": {
    "osm-mcp-server": {
      "command": "uvx",
      "args": [
        "osm-mcp-server"
      ]
    }
  }
  

Features

This server provides LLMs with tools to interact with OpenStreetMap data, enabling location-based applications to:

• Geocode addresses and place names to coordinates
• Reverse geocode coordinates to addresses
• Find nearby points of interest
• Get route directions between locations
• Search for places by category within a bounding box
• Suggest optimal meeting points for multiple people
• Explore areas and get comprehensive location information
• Find schools and educational institutions near a location
• Analyze commute options between home and work
• Locate EV charging stations with connector and power filtering
• Perform neighborhood livability analysis for real estate
• Find parking facilities with availability and fee information

Components

Resources

The server implements location-based resources:

• location://place/{query}: Get information about places by name or address
• location://map/{style}/{z}/{x}/{y}: Get styled map tiles at specified coordinates

Tools

The server implements several geospatial tools:

• geocode_address: Convert text to geographic coordinates
• reverse_geocode: Convert coordinates to human-readable addresses
• find_nearby_places: Discover points of interest near a location
• get_route_directions: Get turn-by-turn directions between locations
• search_category: Find places of specific categories in an area
• suggest_meeting_point: Find optimal meeting spots for multiple people
• explore_area: Get comprehensive data about a neighborhood
• find_schools_nearby: Locate educational institutions near a specific location
• analyze_commute: Compare transportation options between home and work
• find_ev_charging_stations: Locate EV charging infrastructure with filtering
• analyze_neighborhood: Evaluate neighborhood livability for real estate
• find_parking_facilities: Locate parking options near a destination

Local Testing

Running the Server

To run the server locally:

1. Install the package in development mode:

pip install -e .

2. Start the server:

osm-mcp-server

3. The server will start and listen for MCP requests on the standard input/output.

Testing with Example Clients

The repository includes two example clients in the examples/ directory:

Basic Client Example

client.py demonstrates basic usage of the OSM MCP server:

python examples/client.py

This will:

• Connect to the locally running server
• Get information about San Francisco
• Search for restaurants in the area
• Retrieve comprehensive map data with progress tracking

LLM Integration Example

llm_client.py provides a helper class designed for LLM integration:

python examples/llm_client.py

This example shows how an LLM can use the Location Assistant to:

• Get location information from text queries
• Find nearby points of interest
• Get directions between locations
• Find optimal meeting points
• Explore neighborhoods

Writing Your Own Client

To create your own client:

1. Import the MCP client:

from mcp.client import Client

2. Initialize the client with your server URL:

client = Client("http://localhost:8000")

3. Invoke tools or access resources:

# Example: Geocode an

... [View full README on GitHub](https://github.com/jagan-shanmugam/open-streetmap-mcp#readme)