🌍 geo-mcp

Connect Claude or any MCP client to live location intelligence — weather, geocoding, timezone, and nearby places — using only free open APIs.

Live demo on Render • Swagger docs • GitHub repo

What it does

geo-mcp exposes a lightweight MCP surface for real-world geospatial queries. It provides:

• geocode_address — address to latitude/longitude
• reverse_geocode_coords — location to human-readable address
• current_weather — live weather data for any city
• location_timezone — timezone and local time for coordinates
• places_nearby — nearby points of interest from OpenStreetMap

Built for developers, open source, and fast integration with modern tools.

All APIs are free and open — no signup, no keys, no rate-limit surprises for personal use.

Quick start

git clone https://github.com/fjollei/geo-mcp
cd geo-mcp
pip install -r requirements.txt
python server.py

Run with Docker

docker build -t geo-mcp .
docker run -p 8000:8000 geo-mcp

Live demo

Live geo-mcp on Render

Deploy as an HTTP service

This repo now includes app.py, a lightweight HTTP wrapper around the same adapter logic used by the MCP server. It is useful for Render and other container hosts.

• Health check: /healthz
• Swagger UI: /docs
• OpenAPI JSON: /openapi.json
• Reverse proxy docs: /redoc
• Geocode: /geocode?address=...
• Reverse geocode: /reverse-geocode?lat=...&lon=...
• Weather: /weather?city=...
• Timezone: /timezone?lat=...&lon=...
• Nearby places: /places?lat=...&lon=...&category=...&radius_m=...

Connect to Claude Desktop

Add this to your claude_desktop_config.json:

{
  "mcpServers": {
    "geo-mcp": {
      "command": "python",
      "args": ["/absolute/path/to/geo-mcp/server.py"]
    }
  }
}

Config file location:

• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

Restart Claude Desktop — you'll see the 🔨 tools icon appear.

Example prompts

Once connected, try these in Claude:

What's the weather like in Tokyo right now?

Find me hospitals within 500m of the Eiffel Tower.

What time is it right now in lat 35.6762, lon 139.6503?

Geocode "1600 Pennsylvania Ave NW, Washington DC"

Project structure

geo-mcp/
├── server.py              # FastMCP server + tool definitions
├── adapters/
│   ├── geocoding.py       # Nominatim geocoder
│   ├── weather.py         # Open-Meteo weather
│   ├── timezone.py        # timeapi.io timezone
│   └── places.py          # Overpass POI search
├── requirements.txt
├── Dockerfile
└── claude_desktop_config.json

Tool reference

geocode_address(address: str)

{
  "display_name": "Paris, Île-de-France, France",
  "lat": 48.8566,
  "lon": 2.3522,
  "type": "city"
}

current_weather(city: str)

{
  "city": "London",
  "temperature_c": 14.2,
  "feels_like_c": 12.8,
  "humidity_pct": 76,
  "wind_speed_kmh": 18.4,
  "condition": "Partly cloudy",
  "precipitation_mm": 0.0
}

places_nearby(lat, lon, category, radius_m)

Supported categories: restaurant, cafe, hospital, pharmacy, school, supermarket, park, hotel, bank, gas_station

{
  "category": "cafe",
  "count": 8,
  "places": [
    { "name": "Monmouth Coffee", "lat": 51.513, "lon": -0.122, "opening_hours": "Mo-Fr 07:30-18:00" }
  ]
}

Why this project

Built to demonstrate the multi-adapter MCP pattern — the same architecture used in production fleet/telematics MCP servers. Each adapter is:

• Independently testable
• Easily swappable (swap Nominatim for Google Maps, Open-Meteo for OpenWeather, etc.)
• Async-first with httpx
• Typed with clear return schemas

This maps directly to real-world MCP server jobs that require connecting multiple vendor APIs under a unified tool layer.

Extending it

Want to add a new data source? Create adapters/yourapi.py:

import httpx

async def your_tool(param: str) -> dict:
    async with httpx.AsyncClient() as client:
        r = await client.get("https://api.example.com/...", timeout=10)
        r.raise_for_status()
        return r.json()

Then register it in server.py:

from adapters.yourapi import your_tool

@mcp.tool()
async def exposed_tool_name(param: str) -> dict:
    """Tool description shown to the AI."""
    return await your_tool(param)

Tech stack

• FastMCP — MCP server framework
• httpx — async HTTP client
• Open-Meteo — free weather API
• Nominatim — OpenStreetMap geocoding
• Overpass API — OpenStreetMap POI data
• timeapi.io — timezone lookup

License

MIT