# 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](https://github.com/astral-sh/uv) (recommended for dependency management)
- A [Groq](https://console.groq.com/) API Key for the client.
## Installation
1. **Clone the repository:**
```bash
git clone <repository_url>
cd mcpfile
```
2. **Install dependencies:**
Using `uv` (recommended):
```bash
uv sync
```
Or using pip:
```bash
pip install -r requirements.txt
```
*(Note: You may need to generate a `requirements.txt` from `pyproject.toml` if not using `uv`)*
3. **Set up Environment Variables:**
Create a `.env` file in the root directory and add your Groq API key:
```bash
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.
```bash
uv run main.py
# OR
python main.py
```
### 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:
```bash
uv run server/client.py
# OR if using a virtual environment directly:
# python server/client.py
```
3. **Example Interaction:**
```text
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.
```bash
uv run --with mcp[cli] mcp run server/weather.py
```
### Configuration Verification
Ensure that `server/weather.json` points to the correct absolute path of your `server/weather.py` file.
```json
{
"mcpServers": {
"weather": {
"command": "uv",
"args": [
"run",
"--with",
"mcp[cli]",
"mcp",
"run",
"/your/absolute/path/to/mcp/mcpfile/server/weather.py"
]
}
}
}
```
### 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").
