# MySQL

> Use this tool when you need to integrate AI-driven applications with MySQL databases, enabling secure and scalable database access and management. It solves problems related to database operations, such as data storage and retrieval, by providing a bridge between AI assistants and MySQL databases. The tool takes environment-based configuration as input and outputs database operation results, making it suitable for use cases requiring reliable database interactions.

Canonical page: https://skillsregistry.net/skills/xiangma9712-mysql  
JSON: https://api.skillsregistry.net/v1/skills/xiangma9712-mysql

## Description

This MCP server implementation provides a bridge to MySQL databases, enabling AI assistants to perform database operations. It uses TypeScript and Node.js, integrating with the Model Context Protocol SDK and mysql2 library. The server is containerized using Docker and supports environment-based configuration, making it suitable for use cases requiring secure, scalable database access and management in AI-driven applications.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-01

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/xiangma9712-mysql)
- **Repository:** <https://github.com/xiangma9712/mysql-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "xiangma9712-mysql"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/xiangma9712-mysql` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/xiangma9712-mysql/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt