Database-Query-MCP-Server

Here’s a polished, complete README.md you can directly use in your GitHub repository:

📊 MCP Database Query Server

An MCP (Model Context Protocol) server that enables AI assistants like Claude to query real databases (SQLite/PostgreSQL) using natural language.

🚀 Overview

This project acts as a bridge between AI models and databases, allowing users to retrieve data without writing SQL manually.

Instead of writing queries, users can ask:

"Show me all customers who spent over $1000"

The MCP server processes this request, converts it into SQL, executes it, and returns structured results.

🧠 How It Works

1. AI sends a structured request to the MCP server
2. MCP interprets the request
3. Converts it into an SQL query
4. Executes the query on the database
5. Returns results in JSON format

🔁 Example Flow

Input (AI Request)

Show me all customers who spent over $1000

Generated SQL

SELECT * FROM customers WHERE total_spent > 1000;

Output (Response)

[
  {
    "id": 1,
    "name": "John Doe",
    "total_spent": 1500
  }
]

⚙️ Features

• 🔌 MCP protocol integration

• 🗄️ Supports:

  • SQLite
  • PostgreSQL

• 🔍 Natural language query handling

• 📦 JSON-based responses

• 🛡️ Extendable for query validation and security

🛠️ Tech Stack

• Node.js / Python (depending on implementation)
• SQLite / PostgreSQL
• MCP SDK

📁 Project Structure

mcp-database-server/
│── src/
│   ├── server.js / server.py
│   ├── db/
│   │   ├── connection.js
│   │   └── queries.js
│   ├── handlers/
│   │   └── queryHandler.js
│
│── config/
│   └── db.config.js
│
│── package.json / requirements.txt
│── README.md

⚡ Installation

1. Clone the repository

git clone https://github.com/your-username/mcp-database-server.git
cd mcp-database-server

2. Install dependencies

For Node.js:

npm install

For Python:

pip install -r requirements.txt

▶️ Usage

Start the MCP server:

Node.js:

node src/server.js

Python:

python src/server.py

Then connect your AI client (e.g., Claude) to the MCP server.

🎯 Use Cases

• Business analytics

• Admin dashboards

• AI-powered data assistants

• Integration with systems like:

  • Book recommendation platforms
  • Customer management systems

🔒 Future Improvements

• Role-based access control
• Query validation & sanitization
• Natural language → SQL optimization
• Caching for performance
• Logging & monitoring

🤝 Contributing

Contributions are welcome! Feel free to fork the repo and submit a pull request.

📜 License

This project is licensed under the MIT License.