SQLGenius - AI-Powered SQL Assistant MCP Server

@pawankumar94

Basic information

About SQLGenius - AI-Powered SQL Assistant MCP Server

SQLGenius is an AI-powered SQL assistant that converts natural language to SQL queries using Vertex AI's Gemini Pro. Built with MCP and Streamlit, it provides an intuitive interface for BigQuery data exploration with real-time visualization and schema management.

#sqlalchemy #gemini-api #streamlit#vertexai#generative-ai #modelcontextprotocol

SQLGenius - AI-Powered SQL Assistant MCP Server config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

SQLGenius - AI-Powered SQL Assistant MCP Server tools

Tool list not available yet

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Overview

What is SQLGenius?

SQLGenius is an intelligent SQL assistant that helps you query your BigQuery database using natural language. Built with MCP, Vertex AI's Gemini Pro, and Streamlit, it is designed for data analysts and developers who want to interact with their data conversationally.

How to use SQLGenius?

Clone the repository, install dependencies, copy the .env.example to .env, and fill in your BigQuery project and credential details. Start the application with streamlit run streamlit_app.py; the MCP server launches automatically. Use the Streamlit UI tabs to ask natural language questions, write SQL queries directly, or explore your database schema.

Key features of SQLGenius

Natural language to SQL conversion using Gemini Pro
Interactive Streamlit UI with multiple tabs
Real-time query execution and visualization
Database schema explorer
Query history tracking
Safe query validation (only SELECT permitted)

Use cases of SQLGenius

Ask questions about your data in plain English, e.g., "Show me the top 5 customers by revenue"
Write and execute raw SQL queries directly against BigQuery
Browse available tables, view schemas, and see sample data
Track and revisit previously run queries

Frequently asked questions

What MCP tools does SQLGenius expose?

It provides four tools: `execute_nl_query` (natural language query), `execute_sql_query` (raw SQL), `list_tables` (list all tables), and `get_table_schema` (schema for a specific table).

What security restrictions apply?

Only SELECT queries are permitted. Query validation prevents dangerous operations, and error handling with input validation is included.

What are the runtime dependencies?

Python, the packages listed in `requirements.txt`, a Google BigQuery project (PROJECT_ID, DATASET_ID), a service account JSON key, and a Vertex AI location (default `us-central1`).

How do I start the MCP server?

The MCP server starts automatically when you launch the Streamlit app via `streamlit run streamlit_app.py`.

Can I add custom tools?

Yes. Edit the `register_tools()` method in `sql_mcp_server.py`, add your tool using the `@self.tool()` decorator, and restart the server.

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