SQL Server MCP Server

SQL Server MCP Server

Enables AI assistants to interact with SQL Server databases through natural language, providing capabilities for executing queries, exploring schemas, analyzing performance, backing up tables, and managing data with built-in safety limits.

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README

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

  1. Install the "Model Context Protocol" extension
  2. 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

  1. execute_query - Run SQL queries with safety limits
  2. get_schema - Inspect database structure
  3. get_table_info - Detailed table information with samples
  4. explain_query - Query execution plans
  5. check_connection - Database connectivity status
  6. get_table_stats - Table size and performance metrics
  7. search_tables - Find tables and columns by name
  8. backup_table - Create table backups
  9. 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

  1. ODBC Driver Not Found: Install Microsoft ODBC Driver 17 for SQL Server
  2. Connection Failed: Verify server address, credentials, and network connectivity
  3. 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.

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