Geoapify

Demo Model Context Protocol Server for the Geoapify API

python

4

GitHub Stars

python

Language

4 months ago

First Indexed

3 weeks ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs

{
  "mcpServers": {
    "burningion-geoapify-mcp": {
      "command": "uv",
      "args": [
        "--directory",
        "/PATH/TO/THIS/REPO",
        "run",
        "--with",
        "fastmcp",
        "--with",
        "requests",
        "--with",
        "folio",
        "--with",
        "selenium",
        "--with",
        "pillow",
        "fastmcp",
        "run",
        "/PATH/TO/THIS/REPO/server.py"
      ],
      "env": {
        "GEO_APIKEY": "YOURAPIKEY"
      }
    }
  }
}

The Geoapify MCP Server converts addresses into GPS coordinates for mapping and can optionally generate a map image from those coordinates. It helps you programmatically obtain location data and visualize it, integrating GeoJSON as needed for mapping workflows.

How to use

You run the MCP server alongside your MCP client to fetch GPS coordinates from addresses and, if desired, create a map image from those coordinates. The server exposes two core capabilities: (1) retrieving GPS coordinates via the Geoapify API and returning GEOJSON-ready data, and (2) rendering a map image from a GEOJSON file for quick visual verification.

To use these features, you need your Geoapify API key set as an environment variable named GEO_APIKEY. Provide this key when starting the MCP to enable authenticated API access. You can then send requests from your MCP client to obtain coordinates for a list of addresses or to generate a map image from an existing GEOJSON file.

How to install

Prerequisites: you need the MCP runtime environment configured to run stdio-based MCP servers. You will also need a Geoapify API key.

Obtain a Geoapify API key from Geoapify and keep it ready.
Create a configuration entry that runs the MCP server within your environment. The following sample shows how the server is started and how the Geoapify API key is supplied at runtime.

"MCP Map Demo": {
      "command": "uv",
      "args": [
	"--directory",
        "/PATH/TO/THIS/REPO",
        "run",
        "--with",
        "fastmcp",
        "--with",
        "requests",
        "--with",
        "folio",
        "--with",
        "selenium",
        "--with",
        "pillow",
        "fastmcp",
        "run",
        "/PATH/TO/THIS/REPO/server.py"
      ],
      "env": {
        "GEO_APIKEY": "YOURAPIKEY"
      }
    }

Additional sections

Notes about usage, configuration, and capabilities for the Geoapify MCP Server are outlined below to help you integrate it smoothly into your workflow.

Tools and capabilities

get_gps_coordinates — Used to fetch GPS coordinates from the Geoapify API and produce GEOJSON-compatible data.
create_map_from_geojson — Generates a map image from a GEOJSON file. Displaying the map image is supported on macOS in this setup.

Available tools

get_gps_coordinates

Fetch GPS coordinates from the Geoapify API and output GEOJSON-ready data.

create_map_from_geojson

Create a map image from a GEOJSON file; map display is supported on macOS in this setup.