io.github.Souhar-dya/mcp-db-server

Official

by Souhar-dya · Python

MCP Database Server

MCP server for SQLite, PostgreSQL, and MySQL with natural language to SQL and direct SQL tooling.

Database management for SQLite, PostgreSQL, and MySQL with natural language querying.

README.md14 KBView on GitHub

mcp-db-server

An MCP (Model Context Protocol) server that exposes relational databases (PostgreSQL/MySQL) to AI agents with natural language query support. Transform natural language questions into SQL queries and get structured results.

Features

Multi-Database Support: Works with PostgreSQL and MySQL
Natural Language to SQL: Convert plain English queries to SQL using HuggingFace transformers
RESTful API: Clean FastAPI-based endpoints for database operations
Safety First: Read-only operations with query validation and result limits
Docker Ready: Complete containerization with Docker Compose
Production Ready: Health checks, logging, and error handling
AI Agent Friendly: Designed specifically for AI agent integration

API Endpoints

Endpoint	Method	Description
`/health`	GET	Health check and service status
`/mcp/list_tables`	GET	List all available tables with column counts
`/mcp/describe/{table_name}`	GET	Get detailed schema for a specific table
`/mcp/query`	POST	Execute natural language queries
`/mcp/tables/{table_name}/sample`	GET	Get sample data from a table

Quick Start

Option 1: Docker Compose (Recommended)

Clone and start the services:

bash

git clone https://github.com/Souhar-dya/mcp-db-server.git
cd mcp-db-server
docker-compose up --build

Test the endpoints:

bash

# Health check
curl http://localhost:8000/health

# List tables
curl http://localhost:8000/mcp/list_tables

# Describe a table
curl http://localhost:8000/mcp/describe/customers

# Natural language query
curl -X POST "http://localhost:8000/mcp/query" \
  -H "Content-Type: application/json" \
  -d '{"nl_query": "show top 5 customers by total orders"}'

Option 2: Local Development

Prerequisites:
- Python 3.11+
- PostgreSQL or MySQL database
Install dependencies:
bash
```
pip install -r requirements.txt
```

Set environment variables:

bash

export DATABASE_URL="postgresql+asyncpg://user:password@localhost:5432/dbname"
# or for MySQL:
# export DATABASE_URL="mysql+pymysql://user:password@localhost:3306/dbname"

Run the server:
bash
```
python -m app.server
```

Sample Database

The project includes a sample database with realistic e-commerce data:

customers: Customer information (10 sample customers)
orders: Order records (17 sample orders)
order_items: Individual items within orders
order_summary: View combining order and customer data

Natural Language Query Examples

The server can understand various types of natural language queries:

bash

# Get all customers
curl -X POST "http://localhost:8000/mcp/query" \
  -H "Content-Type: application/json" \
  -d '{"nl_query": "show all customers"}'

# Count orders by status
curl -X POST "http://localhost:8000/mcp/query" \
  -H "Content-Type: application/json" \
  -d '{"nl_query": "count orders by status"}'

# Top customers by order value
curl -X POST "http://localhost:8000/mcp/query" \
  -H "Content-Type: application/json" \
  -d '{"nl_query": "top 5 customers by total order amount"}'

# Recent orders
curl -X POST "http://localhost:8000/mcp/query" \
  -H "Content-Type: application/json" \
  -d '{"nl_query": "show recent orders from last week"}'

Configuration

Environment Variables

Variable	Description	Default
`DATABASE_URL`	Full database connection URL	`postgresql+asyncpg://postgres:postgres@localhost:5432/postgres`
`DB_HOST`	Database host	`localhost`
`DB_PORT`	Database port	`5432`
`DB_USER`	Database username	`postgres`
`DB_PASSWORD`	Database password	`postgres`
`DB_NAME`	Database name	`postgres`
`HOST`	Server host	`0.0.0.0`
`PORT`	Server port	`8000`

Database Connection Examples

bash

# PostgreSQL
DATABASE_URL=postgresql+asyncpg://user:pass@localhost:5432/mydb

# MySQL
DATABASE_URL=mysql+pymysql://user:pass@localhost:3306/mydb

# PostgreSQL with SSL
DATABASE_URL=postgresql+asyncpg://user:pass@localhost:5432/mydb?sslmode=require

### Database Connection Examples

```bash
# PostgreSQL (local or cloud)
DATABASE_URL=postgresql+asyncpg://user:password@host:5432/dbname

# MySQL (local or cloud)
DATABASE_URL=mysql+aiomysql://user:password@host:3306/dbname

# PostgreSQL with SSL (cloud, e.g. Neon, Supabase, Aiven)
DATABASE_URL=postgresql+asyncpg://user:password@host:5432/dbname?sslmode=require

# MySQL with SSL (cloud, e.g. Aiven, PlanetScale)
DATABASE_URL=mysql+aiomysql://user:password@host:3306/dbname?ssl-mode=REQUIRED

Note:

For MySQL cloud providers, the ssl-mode parameter in the URL is ignored by the driver, but SSL is always enabled in the MCP server for cloud connections.

For PostgreSQL, use sslmode=require for cloud DBs. For MySQL, just use the standard URL; SSL is handled automatically.

If you see errors about ssl-mode or sslmode, check your URL and ensure you are using the correct driver prefix (mysql+aiomysql or postgresql+asyncpg).

Cloud Database Examples

bash

# Neon (PostgreSQL)
DATABASE_URL=postgresql+asyncpg://username:password@ep-xxxxxx-pooler.us-east-2.aws.neon.tech/dbname

# Aiven (MySQL)
DATABASE_URL=mysql+aiomysql://avnadmin:yourpassword@mysql-xxxxxx-username-xxxx.aivencloud.com:11079/defaultdb?ssl-mode=REQUIRED

Docker Usage with Cloud DB

bash

docker run -d \
  -p 8000:8000 \
  -e DATABASE_URL="<your_cloud_database_url>" \
  souhardyak/mcp-db-server:latest

Troubleshooting

If you get connect() got an unexpected keyword argument 'ssl-mode', ignore it: SSL is still enabled.
For network errors, check firewall and DB credentials.
For MySQL, always use mysql+aiomysql in the URL for async support.

code


## Security Features

- **Read-Only Operations**: Only SELECT queries are allowed
- **Query Validation**: Automatic detection and blocking of dangerous SQL operations
- **Result Limiting**: Maximum 50 rows per query (configurable)
- **Input Sanitization**: Protection against SQL injection
- **Safe Defaults**: Secure configuration out of the box

## Architecture

mcp-db-server/ ├── app/ │ ├── init.py # Package initialization │ ├── server.py # FastAPI application and endpoints │ ├── db.py # Database connection and operations │ └── nl_to_sql.py # Natural language to SQL conversion ├── .github/workflows/ │ └── docker-publish.yml # CI/CD pipeline ├── docker-compose.yml # Docker Compose configuration ├── Dockerfile # Container definition ├── init_db.sql # Sample database schema and data ├── requirements.txt # Python dependencies └── README.md # This file

code


## Model Context Protocol (MCP) Integration

This server is designed to work seamlessly with MCP-compatible AI agents:

1. **Standardized Endpoints**: RESTful API following MCP conventions
2. **Structured Responses**: JSON responses optimized for AI consumption
3. **Error Handling**: Consistent error messages and status codes
4. **Documentation**: OpenAPI/Swagger documentation available at `/docs`

## Publish To VS Code MCP Store (Registry)

VS Code MCP gallery uses MCP Registry metadata. This repository now includes
`server.json` for registry publication.

### 1) Build and publish Docker image

```bash
docker build -t souhardyak/mcp-db-server:1.3.1 .
docker push souhardyak/mcp-db-server:1.3.1

2) Validate server metadata

server.json is configured for an OCI package and stdio transport:

name: io.github.Souhar-dya/mcp-db-server
registryType: oci
identifier: docker.io/souhardyak/mcp-db-server:1.3.1

The Dockerfile includes registry ownership annotation:

io.modelcontextprotocol.server.name=io.github.Souhar-dya/mcp-db-server

3) Publish to MCP Registry

Install publisher and publish metadata:

bash

mcp-publisher login github
mcp-publisher publish

After publishing, users can discover/install it from MCP-compatible clients, including VS Code MCP experiences that read from the registry.

4) Local VS Code config example

json

{
  "servers": {
    "mcp-db-server": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e",
        "DATABASE_URL=sqlite+aiosqlite:////data/default.db",
        "souhardyak/mcp-db-server:1.3.1"
      ]
    }
  }
}

Docker Smoke Test

Use the dedicated Docker smoke test in tests/docker:

bash

python tests/docker/smoke_test.py

This verifies Docker daemon access, image build, container startup, and health status.

Deployment

Docker Hub

bash

# Pull the latest image
docker pull souhardyak/mcp-db-server:latest

# Run with your database
docker run -d \
  -p 8000:8000 \
  -e DATABASE_URL="your_database_url_here" \
  souhardyak/mcp-db-server:latest

Kubernetes

yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: mcp-db-server
spec:
  replicas: 3
  selector:
    matchLabels:
      app: mcp-db-server
  template:
    metadata:
      labels:
        app: mcp-db-server
    spec:
      containers:
        - name: mcp-db-server
          image: souhardyak/mcp-db-server:latest
          ports:
            - containerPort: 8000
          env:
            - name: DATABASE_URL
              valueFrom:
                secretKeyRef:
                  name: db-secret
                  key: url
---
apiVersion: v1
kind: Service
metadata:
  name: mcp-db-server-service
spec:
  selector:
    app: mcp-db-server
  ports:
    - port: 80
      targetPort: 8000
  type: LoadBalancer

Testing

Run Tests Locally

bash

# Start test database
docker-compose up postgres -d

# Wait for database to be ready
sleep 10

# Run tests
python -m pytest tests/ -v

Manual Testing

bash

# Test health endpoint
curl http://localhost:8000/health

# Test table listing
curl http://localhost:8000/mcp/list_tables

# Test natural language query
curl -X POST "http://localhost:8000/mcp/query" \
  -H "Content-Type: application/json" \
  -d '{"nl_query": "show me all customers from California"}'

Contributing

Fork the repository
Create your feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add some amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

📝 Changelog

v1.3.0 (2025-12-24) - Docker Path Fix

Fixed: Resolved import path issues in Docker container causing from db import DatabaseManager to fail
Fixed: Changed relative paths to absolute paths in Dockerfile and docker-compose.yml healthchecks
Improved: mcp_server.py now uses robust path resolution that works both locally and in Docker containers
Updated: Docker image rebuilt and pushed with all path fixes

v1.2.0 (2025-11-03) - MySQL Column Access Fix

Fixed: Resolved Could not locate column in row for column 'column_name' error with MySQL databases
Fixed: Changed describe_table method to use index-based row access for better SQLAlchemy compatibility
Improved: Enhanced cross-database compatibility for schema introspection
Resolved: GitHub Issue #1

v1.1.0 (2025-09-28) - Async Bug Fix

Fixed: Resolved str can't be used in 'await' expression error in MCP server
Improved: NLP query processing now works correctly with Claude Desktop integration
Enhanced: Added comprehensive test database setup scripts
Updated: Docker image rebuilt with bug fixes and updated dependencies

v1.0.0 (2025-09-25) - Initial Release

Initial: Full MCP Database Server implementation
Added: RESTful API with FastAPI
Added: Natural language to SQL conversion
Added: Docker containerization and deployment
Added: Multi-database support (PostgreSQL, MySQL, SQLite)

Acknowledgments

FastAPI for the excellent web framework
HuggingFace Transformers for NL to SQL capabilities
SQLAlchemy for database abstraction
The Model Context Protocol (MCP) community

Support

⭐ If this project helped you, please consider giving it a star!

Install

Configuration

Environment variables

DATABASE_URL

Database connection URL. Defaults to local SQLite in /data/default.db.

claude_desktop_config.json

{
  "mcpServers": {
    "mcp-db-server": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "docker.io/souhardyak/mcp-db-server:1.3.1"
      ],
      "env": {
        "DATABASE_URL": "<YOUR_DATABASE_URL>"
      }
    }
  }
}