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Read-Only SQLite Shop Database MCP Server

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SQLite Database MCP Server

Read-Only SQLite Shop Database MCP Server

An official Model Context Protocol (MCP) server providing secure, read-only database access to an SQLite e-commerce store (shop.db) for AI agents.

๐ŸŒŸ Key Features

  • Standard stdio Transport: Works seamlessly with any MCP client (Claude Desktop, Cursor, Gemini CLI, Antigravity, etc.).
  • Multi-layered Read-Only Security:
    • SQLite URI read-only mode (?mode=ro).
    • Strict runtime PRAGMA query_only = ON;.
    • Pre-flight SQL parser rejecting all DDL/DML mutation statements (INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, etc.).
    • Blocks SQL injection chains and multi-statement execution.
  • LLM-Optimized Tools: Clear descriptions, robust error handling without raw stack traces, and automatic pagination (limit/offset).
  • Flexible Path Resolution: Works out of the box with relative paths, DB_PATH environment variable, or --db-path CLI flag.

๐Ÿ—„๏ธ Database Schema

The SQLite database (shop.db) contains the following entities:

customers
    โ”‚
    โ””โ”€โ”€< orders
             โ”‚
             โ””โ”€โ”€< order_items >โ”€โ”€ products
  • customers: id, first_name, last_name, email, phone, created_at
  • products: id, name, category, price, stock_quantity, created_at
  • orders: id, customer_id, order_date, status (new, processing, shipped, completed, cancelled), total_amount
  • order_items: id, order_id, product_id, quantity, unit_price

๐Ÿ› ๏ธ MCP Tools

Tool Parameters Description
list_tables None Lists all user tables with column count and row count summary.
describe_table table_name (string, required) Returns column definitions, data types, primary keys, foreign keys, row count, and sample rows.
get_database_schema None Returns the complete schema and relationship graph of all tables in one call.
read_query query (string, required), limit (int, default: 100), offset (int, default: 0) Executes read-only queries (SELECT, WITH, EXPLAIN) with pagination.

๐Ÿš€ Getting Started

1. Installation

Create a virtual environment and install the required dependencies:

# Create virtual environment
python3 -m venv .venv
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt

2. Running Locally

Run the MCP server over standard input/output:

python server.py

Or specify a custom database path:

# Using CLI argument
python server.py --db-path /path/to/shop.db

# Or using Environment Variable
DB_PATH=/path/to/shop.db python server.py

3. Running Tests

Run the test suite to verify tool functionality and safety constraints:

python -m unittest discover -s tests -v

๐Ÿ”Œ Connecting to AI Agents

Claude Desktop

Add this server to your claude_desktop_config.json (~/Library/Application Support/Claude/claude_desktop_config.json on macOS or %APPDATA%\Claude\claude_desktop_config.json on Windows):

{
  "mcpServers": {
    "shop-database": {
      "command": "/absolute/path/to/.venv/bin/python",
      "args": ["/absolute/path/to/server.py"],
      "env": {
        "DB_PATH": "/absolute/path/to/shop.db"
      }
    }
  }
}

Cursor IDE

In Cursor Settings โ†’ Features โ†’ MCP:

  • Type: command
  • Command: /absolute/path/to/.venv/bin/python /absolute/path/to/server.py

Antigravity / Gemini CLI

Add to your MCP configuration file:

{
  "mcpServers": {
    "shop-database": {
      "command": "python",
      "args": ["server.py"]
    }
  }
}

๐Ÿ”’ Safety & Validation Examples

If an AI agent or prompt attempts a destructive operation, the server immediately rejects the query gracefully:

  • Prompt: "Delete all cancelled orders."
  • Server Response:
    {
      "error": "Operation rejected: Statement type 'DELETE' is not allowed. Only read-only queries (SELECT, WITH ... SELECT, EXPLAIN) are permitted."
    }
    

๐Ÿ“Š Verification Queries

The server enables AI agents to resolve analytical queries such as:

  1. Table Discovery: list_tables() and describe_table(table_name="customers")
  2. Customer Demographics:
    SELECT count(*) FROM customers WHERE phone LIKE '+7%';
    
  3. Customer Who Spent the Most Money:
    SELECT c.first_name, c.last_name, c.email, SUM(o.total_amount) AS total_spent
    FROM customers c
    JOIN orders o ON c.id = o.customer_id
    WHERE o.status != 'cancelled'
    GROUP BY c.id
    ORDER BY total_spent DESC
    LIMIT 1;
    
  4. Top 5 Best-Selling Products:
    SELECT p.name, SUM(oi.quantity) AS units_sold, SUM(oi.quantity * oi.unit_price) AS revenue
    FROM products p
    JOIN order_items oi ON p.id = oi.product_id
    JOIN orders o ON oi.order_id = o.id
    WHERE o.status != 'cancelled'
    GROUP BY p.id
    ORDER BY units_sold DESC
    LIMIT 5;
    
  5. Top 3 Product Categories by Revenue:
    SELECT p.category, SUM(oi.quantity * oi.unit_price) AS revenue
    FROM products p
    JOIN order_items oi ON p.id = oi.product_id
    JOIN orders o ON oi.order_id = o.id
    WHERE o.status != 'cancelled'
    GROUP BY p.category
    ORDER BY revenue DESC
    LIMIT 3;
    
  6. Customer With Most Orders:
    SELECT c.first_name, c.last_name, COUNT(o.id) AS order_count
    FROM customers c
    JOIN orders o ON c.id = o.customer_id
    GROUP BY c.id
    ORDER BY order_count DESC
    LIMIT 1;
    

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