KNMI Weather MCP

KNMI Weather MCP

A FastMCP server that provides real-time weather data from KNMI weather stations, allowing users to access temperature, humidity, wind speed, and other weather metrics for any location in the Netherlands through natural language queries.

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Location Services
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Python
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Tools

get_location_weather

Get current weather data for a location

search_location

Search for locations in the Netherlands Args: query: Search term for location

get_nearest_station

Find the nearest KNMI weather station to given coordinates Args: latitude: Latitude in degrees longitude: Longitude in degrees

what_is_the_weather_like_in

Get and interpret weather data for a location in the Netherlands Args: location: City or place name in the Netherlands Returns: A natural language interpretation of the current weather conditions

README

KNMI Weather MCP

A FastMCP server that provides real-time weather data from KNMI (Royal Netherlands Meteorological Institute) weather stations. This application fetches the latest 10-minute measurements from the nearest weather station to any location in the Netherlands.

<a href="https://glama.ai/mcp/servers/xanerdcjsm"> <img width="380" height="200" src="https://glama.ai/mcp/servers/xanerdcjsm/badge" alt="KNMI Weather MCP server" /> </a>

Features

  • Get weather data for any location in the Netherlands
  • Automatically finds the nearest KNMI weather station
  • Provides real-time measurements including:
    • Temperature
    • Humidity
    • Wind speed and direction
    • Precipitation
    • Visibility
    • Air pressure
  • Natural language interpretation of weather conditions
  • Location search functionality
  • Detailed logging

Prerequisites

Installation

  1. Clone the repository:

    git clone <repository-url>
    cd knmi-mcp
    
  2. Create a .env file in the project root:

    KNMI_API_KEY=your_api_key_here
    

Running the Server

Using Claude AI

To use this application with Claude AI, run the following command in the folder of the project:

uv run fastmcp install src/knmi_weather_mcp/server.py

This will add the following configuration to your Claude configuration file (typically located at ~/Library/Application Support/Claude/claude_desktop_config.json):

{
    "KNMI Weather": {
      "command": "uv",
      "args": [
        "run",
        "--with",
        "fastmcp",
        "--with",
        "httpx",
        "--with",
        "netCDF4",
        "--with",
        "numpy",
        "--with",
        "pandas",
        "--with",
        "pydantic",
        "--with",
        "python-dotenv",
        "--with",
        "xarray",
        "fastmcp",
        "run",
        "/Users/<username>/<git location>/knmi-mcp/src/knmi_weather_mcp/server.py"
      ]
    }
}

Note: If you see an error like this:

spawn uv ENOENT

Replace the uv command with the full path to the uv command. On *nix systems this can be found with the command which uv.

Manual Running

For development or standalone usage:

uv run fastmcp run src/knmi_weather_mcp/server.py

Available Tools

1. what_is_the_weather_like_in

Get a natural language interpretation of current weather conditions for any location in the Netherlands.

Example:

await what_is_the_weather_like_in("Amsterdam")

2. get_location_weather

Get raw weather data for a location.

Example:

await get_location_weather("Rotterdam")

3. search_location

Search for locations in the Netherlands.

Example:

await search_location("Utrecht")

4. get_nearest_station

Find the nearest KNMI weather station to given coordinates.

Example:

await get_nearest_station(52.3676, 4.9041)

Logging

The application logs are stored in the logs/knmi_weather.log file, providing detailed information about:

  • API requests and responses
  • Weather data processing
  • Error messages
  • Debug information

Data Sources

This application uses the KNMI Data Platform API to fetch data from the "Actuele10mindataKNMIstations" dataset, which provides 10-minute interval measurements from all KNMI weather stations in the Netherlands.

Error Handling

The application includes robust error handling for:

  • Invalid locations
  • API authentication issues
  • Network problems
  • Data parsing errors
  • Missing measurements

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