MSSQL

What is MSSQL MCP Server?

MSSQL MCP Server is a Model Context Protocol (MCP) server designed to provide secure and structured interaction with Microsoft SQL Server (MSSQL) databases. It acts as an intermediary, allowing AI assistants to perform database operations like listing tables, reading content, and executing SQL queries with controlled access and comprehensive logging.

How to use MSSQL MCP Server?

Installation:

pip install mssql-mcp-server

Configuration: Set environment variables for database access:

MSSQL_DRIVER=mssql_driver
MSSQL_HOST=localhost
MSSQL_USER=your_username
MSSQL_PASSWORD=your_password
MSSQL_DATABASE=your_database
#optional
TrustServerCertificate=yes
Trusted_Connection=no

Usage with Claude Desktop: Add the following configuration to claude_desktop_config.json:

{
  "mcpServers": {
    "mssql": {
      "command": "uv",
      "args": [
        "--directory",
        "path/to/mssql_mcp_server",
        "run",
        "mssql_mcp_server"
      ],
      "env": {
        "MSSQL_DRIVER": "mssql_driver",
        "MSSQL_HOST": "localhost",
        "MSSQL_USER": "your_username",
        "MSSQL_PASSWORD": "your_password",
        "MSSQL_DATABASE": "your_database"
      }
    }
  }
}

Running as a Standalone Server:

pip install -r requirements.txt
python -m mssql_mcp_server

Key Features of MSSQL MCP Server

• Secure MSSQL Database Access: Utilizes environment variables for secure connection.
• Controlled Query Execution: Ensures safe execution of SQL queries with robust error handling.
• Table Listing & Data Retrieval: Allows AI assistants to list available tables and retrieve their contents.
• Comprehensive Logging: Provides detailed logs for monitoring all queries and operations.

Use Cases of MSSQL MCP Server

• AI-driven Database Exploration: Enables AI assistants to safely explore and interact with MSSQL databases.
• Automated Data Retrieval: Facilitates automated retrieval of data from MSSQL for various applications.
• Secure Data Operations: Ensures strict permission enforcement and logging for all database interactions, enhancing security.

FAQ about MSSQL MCP Server

Q: What is the primary purpose of MSSQL MCP Server? A: Its primary purpose is to enable secure and structured interaction between AI assistants and MSSQL databases using the Model Context Protocol.

Q: How does MSSQL MCP Server ensure security? A: It ensures security through controlled query execution, comprehensive logging, and adherence to security best practices like using dedicated, least-privileged MSSQL users and environment variables for credentials.

Q: Can I use MSSQL MCP Server with other applications besides Claude Desktop? A: Yes, it can be run as a standalone server, allowing integration with various applications that can interact with a Model Context Protocol server.

Q: What are the recommended security practices when using MSSQL MCP Server? A: It is highly recommended to use a dedicated MSSQL user with minimal privileges, avoid hardcoding credentials, restrict database access to only necessary operations, enable logging and auditing, and regularly review permissions. Always follow the Principle of Least Privilege.

MSSQL MCP Server

MSSQL MCP Server is a Model Context Protocol (MCP) server that enables secure and structured interaction with Microsoft SQL Server (MSSQL) databases. It allows AI assistants to:

• List available tables
• Read table contents
• Execute SQL queries with controlled access

This ensures safer database exploration, strict permission enforcement, and logging of database interactions.

Features

• Secure MSSQL Database Access through environment variables
• Controlled Query Execution with error handling
• Table Listing & Data Retrieval
• Comprehensive Logging for monitoring queries and operations

Installation

pip install mssql-mcp-server

Configuration

Set the following environment variables to configure database access:

MSSQL_DRIVER=mssql_driver
MSSQL_HOST=localhost
MSSQL_USER=your_username
MSSQL_PASSWORD=your_password
MSSQL_DATABASE=your_database
#optional
TrustServerCertificate=yes
Trusted_Connection=no

Usage

With Claude Desktop

To integrate with Claude Desktop, add this configuration to claude_desktop_config.json:

{
  "mcpServers": {
    "mssql": {
      "command": "uv",
      "args": [
        "--directory",
        "path/to/mssql_mcp_server",
        "run",
        "mssql_mcp_server"
      ],
      "env": {
        "MSSQL_DRIVER": "mssql_driver",
        "MSSQL_HOST": "localhost",
        "MSSQL_USER": "your_username",
        "MSSQL_PASSWORD": "your_password",
        "MSSQL_DATABASE": "your_database"
      }
    }
  }
}

Running as a Standalone Server

# Install dependencies
pip install -r requirements.txt

# Run the server
python -m mssql_mcp_server

Development

# Clone the repository
git clone https://github.com/yourusername/mssql_mcp_server.git
cd mssql_mcp_server

# Set up a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install development dependencies
pip install -r requirements-dev.txt

# Run tests
pytest

Security Considerations

• Use a dedicated MSSQL user with minimal privileges.
• Never use root credentials or full administrative accounts.
• Restrict database access to only necessary operations.
• Enable logging and auditing for security monitoring.
• Regularly review permissions to ensure least privilege access.

Security Best Practices

For a secure setup:

1. Create a dedicated MSSQL user with restricted permissions.
2. Avoid hardcoding credentials—use environment variables instead.
3. Restrict access to necessary tables and operations only.
4. Enable SQL Server logging and monitoring for auditing.
5. Review database access regularly to prevent unauthorized access.

For detailed instructions, refer to the MSSQL Security Configuration Guide.

⚠️ IMPORTANT: Always follow the Principle of Least Privilege when configuring database access.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contributing

We welcome contributions! To contribute:

1. Fork the repository.
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Commit your changes: git commit -m 'Add amazing feature'
4. Push to the branch: git push origin feature/amazing-feature
5. Open a Pull Request.

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Need Help?

For any questions or issues, feel free to open a GitHub Issue or reach out to the maintainers.