# SQLite Database MCP Server

## Objective
The **Model Context Protocol (MCP)** is revolutionizing how AI Agents connect to data. In the past, if you wanted an LLM to read your database, you had to write custom glue code, custom prompts, and a custom API.

With MCP, you write a standardized "Server". Once running, *any* MCP-compatible client (like Claude Desktop, an OpenAI agent, or cursor) can instantly connect to it, discover its tools, and query your database without you writing a single prompt!

## Instructions
1. Open `server.py`.
2. Notice we are using the official `mcp.server.fastmcp` module, which makes building an MCP server as easy as building a FastAPI app.
3. Implement `list_tables()`. Use Python's built-in `sqlite3` to connect to `orders.db`, query the `sqlite_master` table, and return a string containing all the table names.
4. Implement `read_query(sql)`. Connect to the database, execute the raw SQL string passed by the LLM, fetch the results, and return them as a formatted string.
5. Notice that `mcp.run()` is called at the bottom. This starts the standard IO (stdio) server loop!
6. Run tests using `pytest`. The test suite will literally spin up an official MCP Client, connect to your server over stdio, and ask it to list its tools and run a query!

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

## Running Tests
```bash
pytest test_server.py
```