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MCP Weather Application (Client-Server)

@RoystonDAlmeida

代码仓库

基本信息

分类

媒体与设计

传输方式

stdio

作者

RoystonDAlmeida

关于 MCP Weather Application

This repository contains files for building an MCP server for weather tasks.

MCP Weather Application 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "mcp-weather-server-roystondalmeida": {
      "command": "uv",
      "args": [
        "run",
        "client.py",
        "../weather/weather.py"
      ]
    }
  }
}

MCP Weather Application 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 MCP Weather Application (Client-Server)?

The MCP Weather Application is a client-server system built with the MCP framework. The server fetches weather data from the National Weather Service (NWS) API via two tools (get_alerts, get_forecast), while the client uses LangChain with the Groq API (Llama 3 model) to process natural language queries and invoke those tools as needed.

How to use MCP Weather Application (Client-Server)?

Detailed setup instructions, including dependency installation and API key configuration, are in each component’s README (weather/README.md, mcp-client/README.md). To run the client and automatically start the server, execute uv run client.py ../weather/weather.py from the mcp-client/ directory. The client connects to the server via stdio.

Key features of MCP Weather Application (Client-Server)

  • Two MCP tools: get_alerts and get_forecast
  • Fetches live data from the National Weather Service API
  • Client uses LangChain and Groq for natural language understanding
  • Full client-server architecture with stdio MCP transport
  • Automatically selects and invokes the correct weather tool

Use cases of MCP Weather Application (Client-Server)

  • Ask for current weather alerts for a given US state
  • Request a detailed forecast for a specific latitude/longitude
  • Use natural language to get weather information without coding
  • Demonstrate MCP client-server interaction with an LLM orchestrator

常见问题

1

What tools does the server provide?

The server exposes two tools: `get_alerts` (for weather alerts by state) and `get_forecast` (for a forecast at given coordinates).

2

Which API does the server use?

It uses the National Weather Service (NWS) API to fetch weather alerts and forecasts.

3

What LLM powers the client’s natural language understanding?

The client uses Groq’s Llama 3 model via LangChain to interpret user queries and decide when to call a server tool.

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