Turbular

Turbular is an open-source Model Context Protocol (MCP) server that enables seamless database connectivity for Language Models (LLMs). It provides a unified API interface to interact with various database types, making it perfect for AI applications that need to work with multiple data sources.

✨ Features

• 🔌 Multi-Database Support: Connect to various database types through a single API
• 🔄 Schema Normalization: Automatically normalize database schemas to correct naming conventions for LLM compatibility
• 🔒 Secure Connections: Support for SSL and various authentication methods
• 🚀 High Performance: Optimizes your LLM generated queries
• 📝 Query Transformation: Let LLM generate queries against normalized layouts and transform them into their unnormalized form
• 🐳 Docker Support: Easy deployment with Docker and Docker Compose
• 🔧 Easy to Extend: Adding new database providers can be easily done by extending the BaseDBConnector interface

🗄️ Supported Databases

| Database Type | Status | Icon | |---------------|--------|----------------------------------------------------------------------------------------------------------------------------------------------------| | PostgreSQL | ✅ | | | MySQL | ✅ | | | SQLite | ✅ | | | BigQuery | ✅ | | | Oracle | ✅ | | | MS SQL | ✅ | | | Redshift | ✅ | |

🚀 Quick Start

Using Docker (Recommended)

1. Clone the repository:

   git clone https://github.com/raeudigerRaeffi/turbular.git
   cd turbular
   

2. Start the development environment:

   docker-compose -f docker-compose.dev.yml up --build
   

3. Test the connection:

   ./scripts/test_connection.py
   

Manual Installation

1. Install Python 3.11 or higher

2. Install dependencies:

   pip install -r requirements.txt
   

3. Run the server:

   uvicorn app.main:app --reload
   

🔌 API Reference

Database Operations

Get Database Schema

POST /get_schema

Retrieve the schema of a connected database for your LLM agent.

Parameters:

• db_info: Database connection arguments
• return_normalize_schema (optional): Return schema in LLM-friendly format

Execute Query

POST /execute_query

Optimizes query and then e

... View full README on GitHub