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Weather-MCP Server

@brunolnetto

代码仓库

基本信息

分类

媒体与设计

传输方式

stdio

作者

brunolnetto

关于 Weather-MCP Server

A MCP server for weather forecast

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

Weather-MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

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

Weather-MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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.

常见问题

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`.

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