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mcp-sqlite-chat

by abdunnasir
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mcp-sqlite-chat

A local AI chat interface that lets you query and manage a SQLite database using plain English.

Built with MCP (Model Context Protocol) + Groq (free LLM). You type natural language questions; the LLM decides which database tools to call; results come back as clean, readable answers.

How It Works

You type a question
        │
        ▼
Groq LLM (llama-3.1-8b-instant)
decides which tools to call
        │
        ▼
MCP Client  ──────────>  MCP Server (server.py)
                                  │
                                  ▼
                            Runs SQL on users.db
        <──────────           Returns result
        │
        ▼
Groq formats a human-readable answer
        │
        ▼
"There are 2 users from London."

The LLM never touches the database directly — all SQL runs through the MCP server.

Related MCP server: MCP Ollama Server

Project Structure

mcp-sqlite-chat/
  server.py       — MCP server: exposes the SQLite DB as tools and resources
  client.py       — Chat interface: connects to the MCP server and Groq
  init_db.py      — Creates users.db with sample data
  db_inspect.py   — Utility to inspect the database directly
  users.db        — SQLite database (generated after running init_db.py)
  requirements.txt
  .env.example

Setup

1. Create and activate a virtual environment

From your project root (e.g. /home/me/my-project/):

python3 -m venv venv
source venv/bin/activate

2. Install dependencies

pip install -r requirements.txt

3. Configure your Groq API key

Copy the example env file and fill in your key:

cp .env.example .env

Edit .env:

GROQ_API_KEY=your-groq-api-key-here

Get a free key at https://console.groq.com

4. Initialize the database

python init_db.py

Expected output:

Database created at: .../users.db
  - 8 users inserted
  - 10 orders inserted

Running

# Make sure the venv is active (from the project root)
source venv/bin/activate

# Start the chat
python client.py

You will see:

Connecting to SQLite MCP server...
Connected. Tools available: ['list_tables', 'describe_table', 'run_query', 'insert_user', 'insert_order']
--------------------------------------------------
SQLite Chat — type your question or 'quit' to exit
--------------------------------------------------

You:

Example Queries

Explore the schema

You: what tables exist?
You: describe the users table
You: what columns does orders have?

Query users

You: show all users
You: how many users are from London?
You: who is the youngest user?
You: list users older than 30

Query orders

You: show all orders
You: what did Bob order?
You: show all orders over $300
You: what is the total revenue?

Join queries

You: who spent the most money in total?
You: show each user and how much they spent
You: which city's users spend the most?

Insert data

You: add user Sara, sara@gmail.com, age 25, from Paris
You: add an order for alice@example.com for a Monitor costing 349.99

Type quit, exit, or q to leave. Ctrl+C also works.

MCP Tools

Tool

Description

list_tables

Lists all tables in the database

describe_table(table_name)

Shows columns and types for a table

run_query(sql)

Runs a SELECT query and returns rows

insert_user(name, email, age, city)

Adds a new user

insert_order(user_email, product, amount)

Adds an order for an existing user

run_query is read-only — only SELECT statements are allowed. All writes go through insert_user and insert_order, which use parameterized queries.

Tech Stack

  • MCP (Model Context Protocol) — tool/resource protocol connecting the client to the server

  • Groq — free, fast LLM inference (llama-3.1-8b-instant)

  • FastMCP — Python framework for building MCP servers

  • SQLite — local database, no server needed

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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