## TODO MCP CLI & Server

This repository contains a minimal Model Context Protocol (MCP) implementation for a to-do list application, including:

- **FastAPI server** (`server/`): exposes a `/tools` endpoint for tool discovery and an `/rpc` endpoint for JSON-RPC calls to perform operations on tasks.
- **CLI client** (`client/cli.py`): a Python command-line interface that interacts with an LLM (via OpenAI) and the MCP server to create, list, and complete tasks using function calls.

---

### Features

- Add tasks with title, content, and optional due date
- List all tasks
- Mark tasks as completed
- Server-side task ID generation
- JSON-RPC 2.0 compliance for tool invocation

---

### Prerequisites

- Python 3.10+
- [pipenv](https://pipenv.pypa.io/) or `venv` for virtual environments
- An OpenAI API key

---

### Installation

1. Clone the repo:

   ```bash
   git clone https://github.com/oseni99/todo-mcp
   cd todo-mcp
   ```

2. Create and activate a virtual environment:

   ```bash
   python3 -m venv .venv
   source .venv/bin/activate
   ```

3. Install dependencies:

   ```bash
   pip install -r requirements.txt
   ```

4. Create a `.env` in the project root:

   ```ini
   OPENAI_API_KEY=sk-...
   MCP_SERVER=http://127.0.0.1:8000
   ```

---

### Directory Structure

```
todoMCP/
├── client/        # CLI client code
│   └── cli.py     # Main entrypoint for the MCP-CLI
├── server/        # FastAPI server code
│   ├── handlers.py    # Business logic for add, list, complete
│   ├── tools.py       # JSON-Schema tool manifest
│   └── main.py        # FastAPI app with /tools and /rpc
├── .env           # Environment variables (not committed)
├── requirements.txt   # Python dependencies
└── README.md      # This file
```

---

### Running the Server

```bash
fastapi dev server/main.py
```

- Visit [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs) for interactive API docs.

---

### Running the CLI

From the project root:

```bash
python -m client.cli
```

Type natural language commands at the prompt, for example:

```text
> Create a task titled "Write blog post" with content "Outline first draft" due 2025-05-20
> List my tasks
> Mark the first task as done
> Thanks!
> exit
```

The CLI will print tool invocations and LLM responses.

---