Aviation Weather

Provides an MCP server that fetches aviation weather data for retrieval by MCP clients.
  • python

0

GitHub Stars

python

Language

7 months ago

First Indexed

3 months 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": {
    "mcdickenson-mcp-demo-aviation-weather": {
      "command": "mcp",
      "args": [
        "dev",
        "src/mcp_aviation_weather/server.py"
      ]
    }
  }
}

You can run and query an MCP Server that fetches aviation weather data to provide up-to-date weather information to MCP clients. This server is designed as a practical example you can deploy locally and integrate with your client workflows to retrieve aviation weather data on demand.

How to use

Start the server using the MCP runner, then connect with your MCP client to request aviation weather data. Once the server is running, your client can request data sources related to aviation weather and receive responses suitable for display or decision making. You can run multiple clients against the same server to fetch different data sets or to test concurrent requests.

To operate effectively, ensure the MCP runtime is installed and available on your system. You willpoint your client at the local server process and perform data requests through your usual MCP client interface. Remember to start the server before issuing any data requests.

How to install

Prerequisites you need to prepare before installing the MCP server.

uv sync

Activate the Python virtual environment you will use for running the server.

source .venv/bin/activate

Run the MCP server using the development command shown in the project setup.

mcp dev src/mcp_aviation_weather/server.py

Notes

This MCP server demonstrates fetching aviation weather data for use by MCP clients. The setup emphasizes a local development workflow you can adapt for testing data retrieval patterns and client integration.

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