MySQL MCP Server

MIT License
19
  • Linux
  • Apple

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Integrations

  • Provides environment variable management for configuring database credentials and server settings through .env files.

  • Supports containerized deployment of the MCP server through Docker, allowing configuration of database connection parameters and port mappings.

  • Includes Mermaid diagram support for visualizing the server architecture and data flow between components.

mysql-mcp-server

ķ•œźµ­ģ–“ README.md

0. Execution

Running with Docker

Change the database connection information as needed.

docker run -d --name mcp-mysql \ -e MYSQL_HOST=localhost \ -e MYSQL_PORT=3306 \ -e MYSQL_USER=root \ -e MYSQL_PASSWORD=mcpTest1234!!! \ -e MYSQL_DATABASE=mcp_test \ -e MCP_PORT=8081 \ -p 3306:3306 mineru/mcp-mysql:1.0.0

Running with Docker Compose

This will proceed with a pre-configured setup.

docker-compose up -d

Running directly with Python

pip install -r requirements.txt python mysql_mcp_server/main.py run

Cursor Configuration

MCP functionality is available from Cursor version 0.46 and above.

Additionally, the MCP feature is only accessible to Cursor Pro account users.

Tool Addition Tips

  • Adding a Tool
    • execute functions implement the actual logic execution (Service Layer).
    • The @tool decorator helps register the tool with MCP (Controller Layer).
  • Explanation
    • Each file under mysql_mcp_server/executors represents a single tool.
    • If a new tool is added, it must be imported in mysql_mcp_server/executors/__init__.py and included in the __all__ array.
    • This ensures the module is automatically registered in the TOOLS_DEFINITION variable.

šŸš§ Development Roadmap šŸš§

  • āš™ļø Parameter Options
    • šŸ”§ Enable/Disable Switch for Each Tool: Provide a function to reduce Input Context costs šŸ’°
    • šŸ”’ Query Security Level Setting: Offer optional control over functions that could damage asset value, such as DROP, DELETE, UPDATE šŸš«
  • āœØ Features
    • šŸ“Š Data Analysis Report Generation: Provide a report generation function optimized for the model to appropriately select various charts based on user requests šŸ“ˆ
      • šŸ“ Reporting capabilities for prescribed forms
      • šŸ–Œļø Diversify report templates
    • šŸ—„ļø Extended Text2SQL Support
    • šŸŒ SSH Connection Support: Enable secure remote access via SSH for advanced operations šŸ”‘
    • šŸ“„ File Extraction Function
      • šŸ“„ CSV
      • šŸ“‘ JSON
      • šŸ“‰ Excel

1. Overview

MCP MySQL Server is a server application for MySQL database operations based on MCP (Model Context Protocol). This server provides tools that allow AI models to interact with the MySQL database.

2. System Configuration

2.1 Key Components

  • MCP Server: A FastMCP server that communicates with AI models
  • MySQL Database: Manages and stores data
  • Tools: Executors that perform database operations

2.2 Tech Stack

  • Language: Python
  • Database: MySQL 8.0
  • Key Libraries:
    • mcp: Implements Model Context Protocol for AI communication
    • PyMySQL: Connects to MySQL and executes queries
    • pandas: Processes and analyzes data
    • python-dotenv: Manages environment variables
    • fire: Implements command-line interfaces

2.3 Deployment Environment

  • Containerized deployment via Docker and Docker Compose
  • Ports: 8081 (MCP Server), 3306 (MySQL)

3. Directory Structure

MCPBoilerPlate/ ā”œā”€ā”€ mysql_mcp_server/ # Main application directory ā”‚ ā”œā”€ā”€ executors/ # Database operation executors ā”‚ ā”‚ ā”œā”€ā”€ create_table.py # Tool for creating tables ā”‚ ā”‚ ā”œā”€ā”€ desc_table.py # Tool for viewing table schema ā”‚ ā”‚ ā”œā”€ā”€ explain.py # Tool for query execution plans ā”‚ ā”‚ ā”œā”€ā”€ insert_query.py # Tool for INSERT query execution ā”‚ ā”‚ ā”œā”€ā”€ insight_starter.py # Schema verification tools for write reports ā”‚ ā”‚ ā”œā”€ā”€ invoke_viz_pro.py # Tool for Visualization chart recommendation ā”‚ ā”‚ ā”œā”€ā”€ select_query.py # Tool for SELECT query execution ā”‚ ā”‚ ā””ā”€ā”€ show_tables.py # Tool for retrieving table lists ā”‚ ā”œā”€ā”€ helper/ # Utility modules ā”‚ ā”‚ ā”œā”€ā”€ db_conn_helper.py # Manages database connections ā”‚ ā”‚ ā”œā”€ā”€ logger_helper.py # Logging utilities ā”‚ ā”‚ ā””ā”€ā”€ tool_decorator.py # Tool decorator ā”‚ ā””ā”€ā”€ main.py # Application entry point ā”œā”€ā”€ docker-compose.yml # Docker Compose configuration ā”œā”€ā”€ Dockerfile # Docker image build settings ā”œā”€ā”€ requirements.txt # Dependency package list ā””ā”€ā”€ .env.example # Example environment variables file

4. Architecture Design

4.1 Layered Structure

  1. Interface Layer: MCP Server (FastMCP)
  2. Business Logic Layer: Handlers and Executors
  3. Data Access Layer: Database connection and query execution

4.2 Key Classes and Modules

  • MySQLMCPServer: Main server class that initializes and runs the MCP server
  • DatabaseManager: Singleton pattern-based database connection manager
  • Executors: Collection of tools for database operations
    • execute_create_table: Creates tables
    • execute_desc_table: Checks table schema
    • execute_explain: Provides query execution plans
    • execute_insert_query: Executes INSETR queries
    • execute_select_query: Executes SELECT queries
    • execute_show_tables: Retrieves table lists

4.3 Communication Flow

  1. AI model requests a list of available tools from the MCP server.
  2. The server returns the available tools list.
  3. The AI model requests the execution of a specific tool.
  4. The server calls the corresponding executor to perform the database operation.
  5. The execution results are returned to the AI model.

5. Scalability and Maintenance

  • Adding Tools: Implement new tools in the executors directory and register them in __init__.py.
  • Environment Configuration: Manage environment variables via the .env file.
  • Logging: Ensure consistent logging using logger_helper.

6. Deployment and Execution

6.1 Local Execution

# Setup environment cp .env.example .env # Modify .env file as needed # Install dependencies pip install -r requirements.txt # Run the server python mysql_mcp_server/main.py run

6.2 Docker Deployment

# Start database using Docker Compose docker-compose up -d db # Build and run mysql-mcp-server with Docker Compose (including rebuilds) docker-compose up -d --build mysql-mcp-server

7. Security Considerations

  • Manage database credentials via environment variables.
  • Use strong passwords in production environments.
  • Consider implementing SSL/TLS encryption for database connections when necessary.