MCP Weather Project

A Model Context Protocol (MCP) server implementation that provides weather alerts via the National Weather Service (NWS) API. This project includes both a FastMCP server and a LangChain-based client with memory capabilities.

Features

• Weather Alerts: Fetch active weather alerts for any US state using the NWS API.

• Echo Resource: A simple resource that echoes back messages.

• Greeting Prompt: A customizable greeting prompt generator.

• Interactive Client: A CLI-based chat client powered by Groq's Llama 3.3 model with conversation memory.

Prerequisites

• Python 3.12 or higher

• uv (recommended for dependency management)

• A Groq API Key for the client.

Installation

1. Clone the repository:

   git clone <repository_url> cd mcpfile

2. Install dependencies: Using uv (recommended):

   uv sync

   Or using pip:

   pip install -r requirements.txt

   (Note: You may need to generate a

3. Set up Environment Variables: Create a .env file in the root directory and add your Groq API key:

   GROQ_API_KEY=your_groq_api_key_here

Usage

Running the Entry Point

The main.py is a simple entry point script that prints a welcome message.

Running the interactive Client

The client connects to the weather server and allows you to interact with it using natural language.

1. Ensure the server configuration in server/weather.json is correct (it points to server/weather.py).

2. Run the client:

   uv run server/client.py # OR if using a virtual environment directly: # python server/client.py

3. Example Interaction:

   You: Check weather alerts for TX Assistant: Checking weather alerts for Texas... [Agent responds with alerts]

Running the MCP Server Standalone

You can run the MCP server directly using uv. This is useful for inspection or debugging with the MCP Inspector.

Configuration Verification

Ensure that server/weather.json points to the correct absolute path of your server/weather.py file.

Project Structure

• server/weather.py: The main MCP server implementation using FastMCP. Defines tools (get_alerts), resources, and prompts.

• server/client.py: An MCP client implementation using LangChain and ChatGroq. Handles the interactive chat session.

• server/weather.json: Configuration file for the MCP client to locate the server.

• main.py: Simple entry point script.

• pyproject.toml: Project configuration and dependencies.

Tools Available

• get_alerts(state: str): Get active weather alerts for a US state (e.g., "CA", "NY").

Resources

• echo://{message}: Echoes a message.

Prompts

• greet_user(name: str, style: str): Generates a greeting in a specified style ("friendly", "formal", or "casual").