What is Agents Sql Mcp

agents_sql_mcp is an AI SQL Assistant that enables users to interact with SQLite databases using natural language queries, powered by Anthropic’s Claude AI.

Use cases

Use cases include generating reports from databases, querying data without needing SQL knowledge, and providing a user-friendly interface for database interactions.

How to use

To use agents_sql_mcp, clone the repository, install the dependencies, set up your Anthropic API key in a .env file, and start the application. Then, access the web interface in your browser to input natural language queries.

Key features

Key features include natural language queries, automatic SQL query generation, query execution against SQLite databases, result formatting, error handling, and example queries to assist users.

Where to use

agents_sql_mcp can be used in various fields such as data analysis, business intelligence, education, and any domain where SQLite databases are utilized.

AI SQL Assistant

A natural language interface for interacting with SQLite databases, powered by Anthropic’s Claude AI.

Overview

This application allows users to interact with SQLite databases using natural language. Instead of writing SQL queries manually, users can ask questions or give instructions in plain English, and the AI will generate and execute the appropriate SQL queries, returning formatted results.

Features

• Natural Language Queries: Ask questions about your data in plain English
• SQL Query Generation: Automatically generates SQL queries based on user input
• Query Execution: Executes the generated queries against a connected SQLite database
• Result Formatting: Displays query results in a readable format
• Error Handling: Provides clear explanations when queries fail
• Example Queries: Includes sample queries to help users get started

Architecture

The application consists of three main components:

1. Web Interface (app.py): A Gradio web interface that allows users to interact with the AI
2. MCP Server (mcp_server.py): A server that handles SQL query execution
3. MCP Client (mcp_client.py): A client that facilitates communication between the web interface and the MCP server

Prerequisites

• Python 3.8+
• An Anthropic API key (to access Claude)

Installation

1. Clone this repository:

   git clone https://github.com/yourusername/ai-sql-assistant.git
   cd ai-sql-assistant
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Create a .env file in the project root with your Anthropic API key:

   ANTHROPIC_API_KEY=your_api_key_here
   

Usage

1. Start the application:

   python app.py
   

2. Open your web browser and navigate to:

   http://localhost:7860
   

3. Type in a natural language query and press Enter or click Submit.

Sample Queries

Here are some example queries you can try:

• “List all tables in the database”
• “Show me all users”
• “Count how many products cost more than $300”
• “What’s the total value of all products in stock?”
• “Insert a new product called ‘Tablet’ with price $499.99 and stock 5”
• “Update the price of Laptop to $1099.99”

Sample Database

The application creates a sample SQLite database with the following tables:

Users Table

• id: INTEGER (Primary Key)
• name: TEXT
• email: TEXT
• created_at: TIMESTAMP

Products Table

• id: INTEGER (Primary Key)
• name: TEXT
• price: REAL
• stock: INTEGER

Technical Details

MCP (Model Completion Protocol)

The application uses MCP to manage communication between Claude and the SQLite database. MCP allows Claude to call functions (tools) and receive results, creating an interactive feedback loop.

Anthropic Claude

The application uses Anthropic’s Claude 3.7 Sonnet model to:

1. Understand natural language queries
2. Generate appropriate SQL queries
3. Explain query results to users

SQLite

The application uses SQLite for database operations. SQLite is:

• Lightweight
• Serverless
• Self-contained
• Zero-configuration

Customization

Connecting to Your Own Database

To use your own SQLite database instead of the sample one:

1. Replace the database initialization in app.py with your own database file path
2. Update the sample table documentation in the UI to match your schema

Modifying the System Prompt

The system prompt that guides Claude’s behavior can be modified in the ChatProcessor class in app.py.

Limitations

• Currently only supports SQLite databases
• Complex queries might require refinement
• Limited error recovery for malformed queries

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.