Weather-MCP Server

@brunolnetto

Repository

Basic information

About Weather-MCP Server

A MCP server for weather forecast

#weather-mcp #weather-forecast#real-time-alerts

Weather-MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "weather_mcp": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

Weather-MCP Server tools

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.

Overview

What is Weather-MCP?

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.

How to use Weather-MCP?

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 – 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.

Key features of Weather-MCP?

Fetch active weather alerts for any U.S. state.
Retrieve detailed weather forecasts by latitude and longitude.
Natural language interaction powered by Pydantic AI.
Extensible toolset built on FastMCP.

Use cases of Weather-MCP?

Ask "Are there any weather alerts for California?" and get a real-time summary.
Request a forecast for a specific coordinate, e.g., 34.05, -118.25.
Embed weather intelligence into a chatbot or voice assistant with few lines of code.

Frequently asked questions

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`.

What data sources does the server use?

The README does not specify the underlying weather data provider; it fetches alerts and forecasts for U.S. locations only.

How do I authenticate with the server?

The server itself does not require authentication. It uses the OpenAI API key to power the LLM used for natural language interaction.

What are the known limits?

No limits are documented in the README. The tools currently cover U.S. weather alerts and forecasts by coordinates.

What transport does the server use?

The server exposes a Server-Sent Events (SSE) endpoint at `http://localhost:8000/sse`.

Comments

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