Is SQL_MCP_Server safe to use?

SQL_MCP_Server has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments.

How do I install SQL_MCP_Server?

SQL_MCP_Server can be installed by cloning its GitHub repository and following the setup instructions in the README.

What can SQL_MCP_Server do?

SQL_MCP_Server provides 4 tools: execute_nl_query, execute_sql_query, list_tables, get_table_schema. See the full tools list on the server page for descriptions and parameters.

What AI clients work with SQL_MCP_Server?

SQL_MCP_Server is compatible with claude-desktop, cursor, claude-code. It uses http transport.

Is SQL_MCP_Server actively maintained?

SQL_MCP_Server is less actively maintained — last commit was 329 days ago. It has 13 GitHub stars.

SQL_MCP_Server

Name: SQL_MCP_Server
Author: pawankumar94

by pawankumar94

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.

13 4 tools GitHub

No known CVEs

No license

Stale

Last commit 329d ago

Works with most clients

Transport: http

4 tools · ~155 tok

Grade A · 0.1% of 200K ctx

Edit this pageView history

Data Analytics

Step 1

Install in your client

Config is the same across clients — only the file and path differ.

Supported in Claude Desktophttp · Node 18+

Paste into ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "sql-mcp-server": {
      "command": "<see-readme>",
      "args": []
    }
  }
}

Are you the author?

Add this badge to your README to show your security score and help users find safe servers.

Embed in your READMEAbout badges →

[![MCPpedia Score](https://mcppedia.org/api/badge/sql-mcp-server)](https://mcppedia.org/s/sql-mcp-server)

Read me

What SQL_MCP_Server does

SQLGenius is an intelligent SQL assistant that helps you query your BigQuery database using natural language. Built with MCP (Model Context Protocol), Vertex AI's Gemini Pro, and Streamlit.

Test This Server

This server supports HTTP transport. Be the first to test it — help the community know if it works.

Loading README…

Scored, not listed

Why this score

Five weighted categories — click any category to see the underlying evidence.

Score breakdown

58/100across 5 weighted dimensions

How we score →

0255075100

−42

Security

Maintenance

Efficiency

Documentation

Compatibility

Categoriesclick a row to see evidence

Security

OSV.dev

No known CVEs.

No package registry to scan.

Inventory

Tools (4)

Click any tool to inspect its schema.

~155 tokens total

Community

Reviews

Be the first to review

Have you used this server?

Share your experience — it helps other developers decide.

How easy was setup?Did it work reliably?How was the documentation?

Frequently Asked Questions

Is SQL_MCP_Server safe to use?: SQL_MCP_Server has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments.
How do I install SQL_MCP_Server?: SQL_MCP_Server can be installed by cloning its GitHub repository and following the setup instructions in the README.
What can SQL_MCP_Server do?: SQL_MCP_Server provides 4 tools: execute_nl_query, execute_sql_query, list_tables, get_table_schema. See the full tools list on the server page for descriptions and parameters.
What AI clients work with SQL_MCP_Server?: SQL_MCP_Server is compatible with claude-desktop, cursor, claude-code. It uses http transport.
Is SQL_MCP_Server actively maintained?: SQL_MCP_Server is less actively maintained — last commit was 329 days ago. It has 13 GitHub stars.

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Community

Discussion

Start a conversation

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Has anyone used this with Cursor?How do you handle auth?Any alternatives?

Edit this pageView history

Data Analytics

Step 1

Install in your client

Config is the same across clients — only the file and path differ.

Supported in Claude Desktophttp · Node 18+

Paste into ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "sql-mcp-server": {
      "command": "<see-readme>",
      "args": []
    }
  }
}

Are you the author?

Add this badge to your README to show your security score and help users find safe servers.

Embed in your READMEAbout badges →

[![MCPpedia Score](https://mcppedia.org/api/badge/sql-mcp-server)](https://mcppedia.org/s/sql-mcp-server)

Read me

What SQL_MCP_Server does

SQLGenius is an intelligent SQL assistant that helps you query your BigQuery database using natural language. Built with MCP (Model Context Protocol), Vertex AI's Gemini Pro, and Streamlit.

Test This Server

This server supports HTTP transport. Be the first to test it — help the community know if it works.

README

SQLGenius - AI-Powered SQL Assistant

SQLGenius is an intelligent SQL assistant that helps you query your BigQuery database using natural language. Built with MCP (Model Context Protocol), Vertex AI's Gemini Pro, and Streamlit.

🌟 Features

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
BigQuery integration
MCP-based architecture

🎥 Demo

Watch SQLGenius in action! Here's a quick demo of how to use the application:

In this demo, you can see:

Natural language query conversion to SQL
Interactive data visualization
Schema exploration
Query history tracking

🚀 Installation

Clone the repository and navigate to the project directory:

cd sql_mcp_server

Install dependencies:

pip install -r requirements.txt

Copy the .env.example file to .env and fill in your configuration:

cp .env.example .env

Set up your environment variables in .env:

PROJECT_ID=your-project-id
DATASET_ID=your-dataset-id
GOOGLE_APPLICATION_CREDENTIALS=path/to/your/service-account.json
VERTEX_AI_LOCATION=us-central1

🎮 Usage

Start the application:

streamlit run streamlit_app.py

The MCP server will start automatically when the Streamlit app launches
Use the tabs to:
- Ask natural language questions about your data
- Write SQL queries directly
- Explore your database schema

📊 Interface Tabs

💬 Natural Language Query

Ask questions in plain English and get SQL results:

"Show me the top 5 customers by revenue"
"What products have the highest sales in January?"
"How many orders were placed last month?"

📊 SQL Query

Write and execute SQL queries directly:

SELECT * FROM orders 
WHERE order_date > '2023-01-01' 
ORDER BY total_amount DESC
LIMIT 10

📋 Database Explorer

Browse available tables
View table schemas
See sample data from any table

🔒 Security Features

Only SELECT queries are permitted
Query validation to prevent dangerous operations
Secure credential management
Error handling and input validation

🛠️ Architecture

SQLGenius uses the Model Context Protocol (MCP) to expose tools that enable:

Natural Language Processing: Convert English questions to SQL
Data Exploration: Fetch schema information and sample data
SQL Execution: Run validated queries against your database

The architecture consists of:

MCP Server: Handles DB connection and provides tools
Streamlit Frontend: User interface for interacting with the system
Vertex AI (Gemini Pro): Powers natural language understanding
BigQuery: Executes SQL queries on your data

📝 MCP Tools

The following MCP tools are available:

execute_nl_query: Execute a natural language query
execute_sql_query: Execute a raw SQL query
list_tables: List all available tables
get_table_schema: Get schema for a specific table

📚 Advanced Usage

To add custom tools to the MCP server:

Edit the register_tools() method in sql_mcp_server.py
Add your custom tool using the @self.tool() decorator
Restart the server

🤝 Contributing

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

Loading README…

Scored, not listed

Why this score

Five weighted categories — click any category to see the underlying evidence.

Score breakdown

58/100across 5 weighted dimensions

How we score →

0255075100

−42

Security

Maintenance

Efficiency

Documentation

Compatibility

Categoriesclick a row to see evidence

Security

OSV.dev

No known CVEs.

No package registry to scan.

Inventory

Tools (4)

Click any tool to inspect its schema.

~155 tokens total

Community

Reviews

Be the first to review

Have you used this server?

Share your experience — it helps other developers decide.

How easy was setup?Did it work reliably?How was the documentation?

Frequently Asked Questions

Is SQL_MCP_Server safe to use?: SQL_MCP_Server has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments.
How do I install SQL_MCP_Server?: SQL_MCP_Server can be installed by cloning its GitHub repository and following the setup instructions in the README.
What can SQL_MCP_Server do?: SQL_MCP_Server provides 4 tools: execute_nl_query, execute_sql_query, list_tables, get_table_schema. See the full tools list on the server page for descriptions and parameters.
What AI clients work with SQL_MCP_Server?: SQL_MCP_Server is compatible with claude-desktop, cursor, claude-code. It uses http transport.
Is SQL_MCP_Server actively maintained?: SQL_MCP_Server is less actively maintained — last commit was 329 days ago. It has 13 GitHub stars.