MCP SQLite Demo

A demonstration of Model Context Protocol (MCP) with a SQLite server and LlamaIndex client integration.

Overview

This project showcases how to build and use an MCP server that exposes SQLite database operations as tools, and connect to it using a LlamaIndex-based client with Ollama LLM support.

Components

• server.py: MCP server that provides SQL tools for managing a SQLite database
• client.py: LlamaIndex client that connects to the MCP server and uses Ollama for natural language interactions

Features

• MCP server with SQLite integration
• Tool-based database operations (add_data, read_data)
• Natural language interface using LlamaIndex and Ollama
• Async support for both server and client

Prerequisites

• Python 3.8+
• Ollama installed and running
• llama3.2 model (or another model that supports tool calling)

Installation

1. Clone this repository:

git clone https://github.com/ELISHA1994/mcp-llama-sqlite-bridge.git
cd mcp-llama-sqlite-bridge

2. Create a virtual environment:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Pull the required Ollama model:

ollama pull llama3.2

Usage

Starting the MCP Server

In one terminal, start the MCP server:

python server.py --server_type=sse

The server will start on http://127.0.0.1:8000 and create a SQLite database (demo.db) with a people table.

Running the Client

In another terminal, run the client:

python client.py

The client will:

1. Connect to the MCP server
2. Display available tools
3. Start an interactive session where you can use natural language to interact with the database

Example Interactions

Enter your message: Add a person named John Doe who is 30 years old and works as an Engineer
Agent: Data has been successfully added to the database.

Enter your message: Show me all people in the database
Agent: Here are all the people in the database:
1. John Doe, 30 years old, Engineer

Database Schema

The SQLite database contains a people table with the following schema:

• id: INTEGER PRIMARY KEY AUTOINCREMENT
• name: TEXT NOT NULL
• age: INTEGER NOT NULL
• profession: TEXT NOT NULL

Available Tools

add_data

Adds new data to the people table using a SQL INSERT query.

Example:

INSERT INTO people (name, age, profession) VALUES ('Alice Smith', 25, 'Developer')

read_data

Reads data from the people table using a SQL SELECT query.

Example:

SELECT * FROM people WHERE age > 25

Troubleshooting

ModuleNotFoundError

If you encounter module import errors, ensure all dependencies are installed:

pip install -r requirements.txt

Ollama Model Error

If you get an error about the model not supporting tools, ensure you're using a model that supports function calling (like llama3.2, mistral, or qwen2.5-coder).

Connection Issues

Ensure the MCP server is running before starting the client.

License

MIT License