About Microsoft SQL Server MCP Server
Microsoft SQL Server MCP Server connects AI assistants to SQL Server for structured database exploration and analysis. It exposes table listing, data reading, and SQL query execution with error handling and environment-variable-based credentials.
Key features
- 01List tables as resources
- 02Read table contents
- 03Execute SQL queries
- 04Handle query errors
- 05Configure credentials through environment variables
- 06Log database operations
Use cases
- 01Explore available database tables
- 02Read records for analysis
- 03Run SQL queries from an AI assistant
MCP support
The MCP server exposes SQL Server tables as resources and provides tools for reading table contents and executing queries to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEMicrosoft SQL Server MCP Server
A Model Context Protocol (MCP) server that enables secure interaction with Microsoft SQL Server databases. This server allows AI assistants to list tables, read data, and execute SQL queries through a controlled interface, making database exploration and analysis safer and more structured.
Features
- List available SQL Server tables as resources
- Read table contents
- Execute SQL queries with proper error handling
- Secure database access through environment variables
- Comprehensive logging
- Automatic system dependency installation
Installation
The package will automatically install required system dependencies (like FreeTDS) when installed through MCP:
pip install mssql-mcp-server
Configuration
Set the following environment variables:
MSSQL_SERVER=localhost
MSSQL_USER=your_username
MSSQL_PASSWORD=your_password
MSSQL_DATABASE=your_database
Usage
With Claude Desktop
Add this to your claude_desktop_config.json:
{
"mcpServers": {
"mssql": {
"command": "uv",
"args": [
"--directory",
"path/to/mssql_mcp_server",
"run",
"mssql_mcp_server"
],
"env": {
"MSSQL_SERVER": "localhost",
"MSSQL_USER": "your_username",
"MSSQL_PASSWORD": "your_password",
"MSSQL_DATABASE": "your_database"
}
}
}
}
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/RichardHan/mssql_mcp_server.git
cd mssql_mcp_server
# Create virtual environment
python -m venv venv
source venv/bin/activate # or `venv\Scripts\activate` on Windows
# Install development dependencies
pip install -r requirements-dev.txt
# Run tests
pytest
Security Considerations
- Never commit environment variables or credentials
- Use a database user with minimal required permissions
- Consider implementing query whitelisting for production use
- Monitor and log all database operations
Security Best Practices
This MCP server requires database access to function. For security:
- Create a dedicated SQL Server login with minimal permissions
- Never use sa credentials or administrative accounts
- Restrict database access to only necessary operations
- Enable logging for audit purposes
- Regular security reviews of database access
See SQL Server Security Configuration Guide for detailed instructions on:
- Creating a restricted SQL Server login
- Setting appropriate permissions
- Monitoring database access
- Security best practices
⚠️ IMPORTANT: Always follow the principle of least privilege when configuring database access.
License
MIT License - see LICENSE file for details.
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
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.