awslabs.mysql-mcp-server 1.0.6

An AWS Labs Model Context Protocol (MCP) server for mysql

AWS Labs MySQL MCP Server

An AWS Labs Model Context Protocol (MCP) server for Aurora MySQL

Features

Natural language to MySQL SQL query

• Converting human-readable questions and commands into structured MySQL-compatible SQL queries and executing them against the configured Aurora MySQL database.

Prerequisites

1. Install uv from Astral or the GitHub README
2. Install Python using uv python install 3.10
3. Aurora MySQL Cluster with MySQL username and password stored in AWS Secrets Manager
4. Enable RDS Data API for your Aurora MySQL Cluster, see instructions here
5. This MCP server can only be run locally on the same host as your LLM client.
6. Docker runtime
7. Set up AWS credentials with access to AWS services
   • You need an AWS account with appropriate permissions
   • Configure AWS credentials with aws configure or environment variables

Installation

Cursor	VS Code

Configure the MCP server in your MCP client configuration (e.g., for Amazon Q Developer CLI, edit ~/.aws/amazonq/mcp.json):

{
  "mcpServers": {
    "awslabs.mysql-mcp-server": {
      "command": "uvx",
      "args": [
        "awslabs.mysql-mcp-server@latest",
        "--resource_arn", "[your data]",
        "--secret_arn", "[your data]",
        "--database", "[your data]",
        "--region", "[your data]",
        "--readonly", "True"
      ],
      "env": {
        "AWS_PROFILE": "your-aws-profile",
        "AWS_REGION": "us-east-1",
        "FASTMCP_LOG_LEVEL": "ERROR"
      },
      "disabled": false,
      "autoApprove": []
    }
  }
}

Windows Installation

For Windows users, the MCP server configuration format is slightly different:

{
  "mcpServers": {
    "awslabs.mysql-mcp-server": {
      "disabled": false,
      "timeout": 60,
      "type": "stdio",
      "command": "uv",
      "args": [
        "tool",
        "run",
        "--from",
        "awslabs.mysql-mcp-server@latest",
        "awslabs.mysql-mcp-server.exe"
      ],
      "env": {
        "FASTMCP_LOG_LEVEL": "ERROR",
        "AWS_PROFILE": "your-aws-profile",
        "AWS_REGION": "us-east-1"
      }
    }
  }
}

Build and install docker image locally on the same host of your LLM client

1. 'git clone https://github.com/awslabs/mcp.git'
2. Go to sub-directory 'src/mysql-mcp-server/'
3. Run 'docker build -t awslabs/mysql-mcp-server:latest .'

Add or update your LLM client's config with following:

{
  "mcpServers": {
    "awslabs.mysql-mcp-server": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "-e", "AWS_ACCESS_KEY_ID=[your data]",
        "-e", "AWS_SECRET_ACCESS_KEY=[your data]",
        "-e", "AWS_REGION=[your data]",
        "awslabs/mysql-mcp-server:latest",
        "--resource_arn", "[your data]",
        "--secret_arn", "[your data]",
        "--database", "[your data]",
        "--region", "[your data]",
        "--readonly", "True"
      ]
    }
  }
}

NOTE: By default, only read-only queries are allowed and it is controlled by --readonly parameter above. Set it to False if you also want to allow writable DML or DDL.

AWS Authentication

The MCP server uses the AWS profile specified in the AWS_PROFILE environment variable. If not provided, it defaults to the "default" profile in your AWS configuration file.

"env": {
  "AWS_PROFILE": "your-aws-profile"
}

Make sure the AWS profile has permissions to access the RDS data API, and the secret from AWS Secrets Manager. The MCP server creates a boto3 session using the specified profile to authenticate with AWS services. Your AWS IAM credentials remain on your local machine and are strictly used for accessing AWS services.