SQL Server MCP Server

A Model Context Protocol (MCP) server that provides AI assistants with SQL Server database access capabilities.

Features

Execute SQL queries with automatic safety limits
Database schema inspection and exploration
Table statistics and performance monitoring
Advanced search capabilities for tables and columns
Table backup functionality
Data insertion with conflict handling
Query execution plan analysis
Connection health monitoring

Quick Start

1. Setup Environment

# Navigate to project directory
cd C:\Users\benha\Desktop\sql-server-mcp

# Create virtual environment
python -m venv venv
venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

2. Configure Database Connection

Edit the .env file with your SQL Server credentials:

SQL_SERVER_HOST=192.168.1.117
SQL_SERVER_DATABASE=EM_Data
SQL_SERVER_USERNAME=benhg
SQL_SERVER_PASSWORD=your_actual_password
SQL_SERVER_PORT=1433

3. Test the Server

python -m sql_server_mcp.server

Integration with AI Tools

Claude Desktop

Add to your Claude Desktop configuration file:

Location:

Windows: %APPDATA%\Claude\claude_desktop_config.json
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

Configuration:

{
  "mcpServers": {
    "sql-server": {
      "command": "python",
      "args": ["-m", "sql_server_mcp.server"],
      "cwd": "C:\\Users\\benha\\Desktop\\sql-server-mcp",
      "env": {
        "SQL_SERVER_HOST": "192.168.1.117",
        "SQL_SERVER_DATABASE": "EM_Data",
        "SQL_SERVER_USERNAME": "benhg",
        "SQL_SERVER_PASSWORD": "your_password_here",
        "SQL_SERVER_PORT": "1433"
      }
    }
  }
}

VS Code

Install the "Model Context Protocol" extension
Add to VS Code settings.json:

{
  "mcp.servers": {
    "sql-server": {
      "command": "python",
      "args": ["-m", "sql_server_mcp.server"],
      "cwd": "C:\\Users\\benha\\Desktop\\sql-server-mcp"
    }
  }
}

Cursor

Add to Cursor MCP configuration:

{
  "mcp": {
    "servers": {
      "sql-server": {
        "command": "python",
        "args": ["-m", "sql_server_mcp.server"],
        "cwd": "C:\\Users\\benha\\Desktop\\sql-server-mcp"
      }
    }
  }
}

Available Tools

execute_query - Run SQL queries with safety limits
get_schema - Inspect database structure
get_table_info - Detailed table information with samples
explain_query - Query execution plans
check_connection - Database connectivity status
get_table_stats - Table size and performance metrics
search_tables - Find tables and columns by name
backup_table - Create table backups
insert_data - Insert data with conflict handling

Usage Examples

Once integrated with Claude, you can ask:

"Show me the schema of my SeriesRecord table"
"Execute: SELECT TOP 10 * FROM SeriesRecord WHERE Source = 'NBP'"
"What tables do I have in my database?"
"Create a backup of my SeriesRecord table"
"Search for any tables containing 'GDP'"
"Show me statistics for all my tables"

Security Features

Automatic query limits (TOP 1000 by default)
Parameterized query support
Environment-based configuration
Connection pooling and health checks
Comprehensive error handling

Development

Running Tests

pip install pytest pytest-asyncio
pytest tests/

Project Structure

sql-server-mcp/
├── sql_server_mcp/
│   ├── __init__.py
│   └── server.py
├── tests/
│   ├── __init__.py
│   └── test_server.py
├── requirements.txt
├── pyproject.toml
├── .env
└── README.md

Troubleshooting

Common Issues

ODBC Driver Not Found: Install Microsoft ODBC Driver 17 for SQL Server
Connection Failed: Verify server address, credentials, and network connectivity
Permission Denied: Ensure database user has appropriate permissions

Testing Connection

# Test ODBC drivers
import pyodbc
print(pyodbc.drivers())

# Test basic connection
from sqlalchemy import create_engine, text
engine = create_engine('mssql+pyodbc://user@server:port/database?driver=ODBC+Driver+17+for+SQL+Server')
with engine.connect() as conn:
    result = conn.execute(text('SELECT 1'))
    print('Connection successful!')

License

MIT License - see LICENSE file for details.