MCP-AI2SQL

A Python project that provides tools for generating SQL queries through a FastMCP server interface in Cursor IDE.

Features

• SQL Query Generation: Generate SQL queries based on natural language requests
• FastMCP Server: Runs as a server that can be queried for these tools
• Cursor Integration: Works seamlessly with Cursor IDE through MCP configuration
• Claude Integration: Compatible with Claude AI assistant for natural language SQL query generation

Prerequisites

• Python 3.10 or higher
• UV package manager
• Dependencies listed in pyproject.toml
• Cursor IDE

Installation

Using UV Package Manager (Recommended)

1. Create a new project

uv init mcp-ai2sql
cd mcp-ai2sql

2. Create and activate virtual environment

# Create virtual env
uv venv

# Activate for macOS/Linux
source .venv/bin/activate

# Activate for Windows
.venv\Scripts\activate

3. Install dependencies

uv add "mcp[cli]" dotenv

Alternative Installation Method

1. Clone this repository

git clone https://github.com/yourusername/mcp-ai2sql.git
cd mcp-ai2sql

2. Set up a virtual environment

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

3. Install dependencies

pip install -e .

Usage

Run the MCP server:

python main.py

Cursor IDE Integration

To use MCP-AI2SQL with Cursor IDE, configure the MCP server in ~/.cursor/mcp.json:

{
  "mcpServers": {
    "mcp-ai2sql": {
      "command": "/path/to/your/python/uv",
      "args": [
        "--directory",
        "/path/to/mcp-ai2sql",
        "run",
        "main.py"
      ]
    }
  }
}

Replace the paths with your actual Python/UV path and project directory.

Claude App Integration

MCP-AI2SQL can be used with Claude AI assistant for more intuitive SQL query generation:

1. Make sure your MCP server is running
2. In Claude's interface, you can request SQL queries in natural language
3. Claude will utilize the MCP-AI2SQL tool to generate accurate SQL based on your descriptions

Example prompt for Claude:

Use the AI2SQL tool to create a query that finds all customers who placed orders in the last month.

Claude will process this request and generate the appropriate SQL using the MCP-AI2SQL backend.

Available Tools

SQL Generator Tool

Generate SQL queries from natural language:

generate_sql(
    request="find all users", 
    table_name="users", 
    columns="id, name, email"
)

Supports various SQL operations:

• SELECT queries
• CREATE TABLE statements
• INSERT statements
• UPDATE statements
• DELETE statements
• DROP TABLE statements

Environment Variables

Create a .env file in the root directory with the following variables:

# Add any environment variables needed here

Project Structure

• main.py - Main server implementation with tool definitions
• pyproject.toml - Project configuration and dependencies

License

MIT License

Copyright (c) 2023 Mustafa Ergisi

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Contributing

Contributions are welcome! Here's how you can contribute to MCP-AI2SQL:

1. Fork the repository: Create your own fork of the project on GitHub
2. Create a branch: Make your changes in a new branch

   git checkout -b feature/your-feature-name

3. Commit your changes: Make sure to write clear, concise commit messages

   git commit -m "Add feature: brief description of changes"

4. Push to your branch: Upload your changes to GitHub

   git push origin feature/your-feature-name

5. Submit a pull request: Create a PR from your branch to the main repository

Development Guidelines

• Follow PEP 8 style guidelines for Python code
• Write tests for new features
• Update documentation when implementing new features
• Add docstrings to functions and classes

Reporting Issues

If you find a bug or have a feature request, please create an issue on the GitHub repository. Include:

• A clear, descriptive title
• Steps to reproduce the issue
• Expected and actual behavior
• Screenshots if applicable
• Any relevant logs or error messages