Which integrations are available for this server?

Provides geocoding (address to coordinates), reverse geocoding (coordinates to address), and nearby places search using OpenStreetMap data.

How do I use geo-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@geo-mcp What's the weather in Tokyo?" 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.

🌍 geo-mcp

A geospatial MCP server that gives Claude (or any MCP client) real-world location superpowers — weather, geocoding, timezone, and nearby places. Zero API keys required.

What it does

Connect Claude Desktop, Cursor, or any MCP client to live geospatial data through 5 clean tools:

Tool	Description	API Used
`geocode_address`	Address → lat/lon	Nominatim (OSM)
`reverse_geocode_coords`	lat/lon → address	Nominatim (OSM)
`current_weather`	Live weather for any city	Open-Meteo
`location_timezone`	Timezone + local time	timeapi.io
`places_nearby`	POIs within a radius	Overpass (OSM)

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

Quick start

git clone https://github.com/yourname/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

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

This server cannot be installed

F

license - not found

-

quality - not tested

C

maintenance

How are these scores calculated?

Resources

GitHub Repository

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