MCP.so
ログイン

Weather-MCP Server

@brunolnetto

基本情報

カテゴリ

メディアとデザイン

トランスポート

stdio

作者

brunolnetto

Weather-MCP Server について

A MCP server for weather forecast

Weather-MCP Server の設定

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"
      ]
    }
  }
}

Weather-MCP Server のツール

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。

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.

よくある質問

1

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`.

2

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.

3

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.

4

What are the known limits?

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

5

What transport does the server use?

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

コメント

「メディアとデザイン」の他のコンテンツ