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🌦️ Weather-MCP

@brunolnetto

🌦️ Weather-MCP について

A MCP server for weather forecast

基本情報

カテゴリ

メディアとデザイン

ランタイム

python

トランスポート

stdio

公開者

brunolnetto

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

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

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

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.

FAQ from Weather-MCP

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.

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