What are the dependencies and runtime requirements?
Python 3.8 or higher, an OpenAI API key (`OPENAI_API_KEY`), and dependencies installed via `uv sync`.
@brunolnetto
Basic information
A MCP server for weather forecast
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"weather_mcp": {
"command": "uv",
"args": [
"venv"
]
}
}
}Tool list not available yet
This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Weather-MCP is a FastAPI server that integrates with FastMCP and Pydantic AI to provide real-time weather alerts and forecasts for U.S. locations. It is designed for developers who want to enable natural language weather queries in their AI applications.
Clone the repository, set up a virtual environment with uv, install dependencies, and set the OPENAI_API_KEY environment variable. Start the server with python weather_server.py β it runs at http://localhost:8000/sse. Interact via a Pydantic AI agent (e.g., agent.run("Are there any weather alerts for California?")) or directly through the FastMCP client.
34.05, -118.25.Python 3.8 or higher, an OpenAI API key (`OPENAI_API_KEY`), and dependencies installed via `uv sync`.
The README does not specify the underlying weather data provider; it fetches alerts and forecasts for U.S. locations only.
The server itself does not require authentication. It uses the OpenAI API key to power the LLM used for natural language interaction.
No limits are documented in the README. The tools currently cover U.S. weather alerts and forecasts by coordinates.
The server exposes a Server-Sent Events (SSE) endpoint at `http://localhost:8000/sse`.

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