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weather-forecast-server: MCP server for weather forecast

Project description

Weather Forecast MCP Server

A Model Context Protocol (MCP) server for retrieving weather information using the wttr.in service.

Overview

This MCP server provides tools for accessing current weather conditions and forecasts for locations worldwide. It can be easily integrated with MCP clients, including Claude and other LLM applications supporting the MCP protocol.

Features

  • Get current weather for any location
  • Get multi-day weather forecasts (up to 3 days)
  • Support for both Chinsee/English and other language location names
  • Easy integration with MCP client applications

Installation

You can install the MCP Weather Server using uv:

uv install weather-forecast-server

Or using pip:

pip install weather-forecast-server

Usage

Running as a standalone server

Run the server with the default transport (stdio):

uv run weather-forecast-server

Or specify a transport type:

uv run weather-forecast-server --transport sse

Integrating with Claude Desktop

To add the weather server to Claude Desktop:

uv run mcp install weather-forecast-server --name "Weather Tool"

Tools available

  1. get_weather - Get current weather conditions for a location (up to 3 days)

Example

Using the server with the MCP CLI:

# Start the MCP inspector for testing
uv run mcp dev weather-forecast-server

Development

To set up a development environment:

git clone https://github.com/shibing624/mcp-server-weather.git
cd weather-forecast-server

uv venv
uv pip install -e .

Contact

  • Issues and suggestions: GitHub issues
  • Email: xuming624@qq.com
  • WeChat: Add me (WeChat ID: xuming624) with the message: "Name-Company-NLP" to join our NLP discussion group.

License

This project is licensed under The Apache License 2.0 and can be used freely for commercial purposes. Please include a link to codev and the license in your product documentation.

Contribute

We welcome contributions to improve this project! Before submitting a pull request, please:

  1. Add appropriate unit tests in the tests directory
  2. Run python -m pytest to ensure all tests pass
  3. Submit your PR with clear descriptions of the changes

Acknowledgements

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