MSSQL MCP Server

What does “MSSQL” MCP Server do?

MSSQL MCP Server is a tool designed to bridge AI assistants with Microsoft SQL Server databases, enabling advanced database interaction and business intelligence directly from AI workflows. Through the Model Context Protocol (MCP), it facilitates seamless execution of SQL queries, business data analysis, and the generation of business insight memos. This server empowers AI agents and developers to perform tasks such as reading and writing database records, managing database schema, and extracting actionable insights, thereby streamlining database operations and automating business intelligence tasks. By connecting external data sources to AI assistants, MSSQL MCP Server significantly enhances development workflows and enables intelligent, context-aware automation in enterprise environments.

List of Prompts

No prompt templates are explicitly mentioned in the repository or documentation.

List of Resources

No explicit MCP resources are listed in the repository’s documentation.

List of Tools

• read_query
  Execute SELECT queries to read data from the SQL Server database.
• write_query
  Execute INSERT, UPDATE, or DELETE queries to modify database records.
• create_table
  Create new tables within the SQL Server database.
• list_tables
  Retrieve a list of all tables present in the database.
• describe-table
  View schema information for a specific table.
• append_insight
  Add new business insights to the memo resource.

Use Cases of this MCP Server

• Database Management
  Enables AI agents to read, write, and manage SQL Server databases, facilitating CRUD (Create, Read, Update, Delete) operations programmatically for streamlined data handling.
• Business Data Analysis
  Allows the execution of analytical queries to extract, aggregate, and analyze business data, which aids in generating actionable business intelligence.
• Schema Exploration
  Provides tools to list tables and describe table schemas, enabling thorough exploration and documentation of the database structure.
• Automated Business Insight Generation
  The append_insight tool can be used to automatically generate and log business insight memos based on analyzed data, supporting business decision-making.
• Integration with AI Development Tools
  Can be integrated into environments like Claude, Windsurf, Cursor, and Cline to enhance workflow automation and facilitate the testing and deployment of AI-driven database applications.

How to set it up

Windsurf

1. Prerequisites: Ensure Python 3.x is installed along with required packages (pyodbc, pydantic, mcp). Install with pip install -r requirements.txt.

2. Configure Database: Create a config.json file in the same directory as server.py with your SQL Server connection details (see config example below).

3. Edit Configuration: Add the following entry to your Windsurf (or Claude Desktop) config file:

   {
     "mcpServers": {
       "mssql": {
         "command": "python",
         "args": [
           "~/server.py"
         ]
       }
     }
   }
   

4. Save and Restart: Save the configuration file and restart Windsurf.

5. Verify Setup: Ensure the MCP server is running and accessible from Windsurf.

Claude

1. Install Requirements: Ensure dependencies are installed as per requirements.txt.

2. Database Config: Create and fill out config.json as shown below.

3. Add MCP Server: In claude_desktop_config.json, add:

   {
     "mcpServers": {
       "mssql": {
         "command": "python",
         "args": [
           "~/server.py"
         ]
       }
     }
   }
   

4. Restart Claude Desktop: Restart to load the new configuration.

5. Test Connection: Confirm connection to the MSSQL MCP server.

Cursor

1. Install Dependencies: Use pip install -r requirements.txt.

2. Configure Database: Create config.json with your SQL Server settings.

3. Add MCP Server in Cursor: In the MCP configuration panel, add:

   {
     "mcpServers": {
       "mssql": {
         "command": "python",
         "args": [
           "~/server.py"
         ]
       }
     }
   }
   

4. Save/Restart: Save changes and restart Cursor.

5. Verify: Confirm the MCP server is recognized in Cursor.

Cline

No explicit instructions provided for Cline. You may adapt the above process using the same JSON configuration method.

Example config.json for Database Connection

{
  "database": {
    "driver": "ODBC Driver 17 for SQL Server",
    "server": "server ip",
    "database": "db name",
    "username": "username",
    "password": "password",
    "trusted_connection": false
  },
  "server": {
    "name": "mssql-manager",
    "version": "0.1.0"
  }
}

Securing API Keys Using Environment Variables

No explicit mention of API key handling or environment variable usage in the repository documentation. Make sure to set sensitive credentials (like username and password) via environment variables if supported by your deployment. Example placeholder:

{
  "database": {
    "username": "${MSSQL_USER}",
    "password": "${MSSQL_PASS}"
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "mssql": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “mssql” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Our opinion

MSSQL MCP Server provides a solid suite of database tools and example configurations for major platforms, but lacks explicit MCP prompt/resource definitions and security/env var guidance. It is highly useful for SQL Server automation, but would benefit from richer documentation and security best practices.

Rating: 6/10 — Good core functionality and open source, but missing some advanced MCP features and documentation depth.

MCP Score