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
基本情報
A MCP server for weather forecast
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"
]
}
}
}ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
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。
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 – 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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