Weather MCP Server

This is a Model Context Protocol (MCP) server that provides weather information using the National Weather Service (NWS) API.

Features

• Get weather alerts for a US state
• Get weather forecast for a specific location (using latitude and longitude)

Requirements

• Python 3.10+
• FastMCP
• httpx

Installation

1. Clone this repository
2. Set up a virtual environment:
   python -m venv .venv source .venv/bin/activate # On Windows, use `.venv\Scripts\activate`
3. Install the required packages using uv:
   uv add "mcp[cli]" httpx

Configuration

The server uses a configuration file config.py with the following settings:

• NWS_API_BASE: The base URL for the National Weather Service API
• USER_AGENT: The User-Agent string used when making requests to the NWS API
• LOG_LEVEL: The logging level (e.g., "INFO", "DEBUG")
• LOG_FORMAT: The format string for log messages
• REQUEST_TIMEOUT: The timeout for API requests in seconds

You can modify these settings in the config.py file to customize the server behavior.

Usage

Running the server standalone

To run the server standalone:

1. Activate the virtual environment if not already activated:
   source .venv/bin/activate # On Windows, use `.venv\Scripts\activate`
2. Run the server:
   python weather.py

Using with Cline

The Weather MCP Server has been added to the Cline configuration. To use it within Cline:

1. Ensure that Cline is properly set up and running.
2. The Weather MCP Server will be available as a tool named "weather".
3. You can use the following tools within Cline:a. get_alerts(state: str): Get weather alerts for a US state (use two-letter state code, e.g., "CA" for California) b. get_forecast(latitude: float, longitude: float): Get weather forecast for a specific location

Example usage in Cline:

Note: The exact syntax for calling MCP tools may vary depending on your Cline setup. Refer to Cline documentation for the most up-to-date usage instructions.

Error Handling and Logging

The server includes improved error handling for API requests and logging. If an error occurs during a request, the server will log the error and return an appropriate error message. Logs are printed to the console with the configured log level and format.

Testing

Unit Tests

To run the unit tests:

These tests cover the basic functionality of the get_alerts and get_forecast tools.

Manual Testing

To manually test the server, you can use the MCP client to call the provided tools. Here are some example commands:

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is open source and available under the MIT License.