davewind/mysql-mcp-server
by Various
mcp model-context-protocol mysql cursor n8n
MCP
davewind/mysql-mcp-server
Added 1 June 2026
Overview
A Model Context Protocol (MCP) server for MySQL databases, written in JavaScript. It enables AI assistants like Cursor and n8n to execute SQL queries and interact with MySQL through the MCP standard. The server acts as a bridge between AI models and MySQL, allowing natural language database operations.
Best for
Best for
Developers prototyping AI agents that need simple MySQL access via MCP
Use cases
- Query MySQL databases from AI coding assistants like Cursor
- Integrate MySQL data retrieval into n8n AI workflows
- Build custom AI agents that can read and write to MySQL
How to use
Install
npm install @davewind/mysql-mcp-server -g Tools exposed
query
Example client config
{\n "mcpServers": {\n "mysql": {\n "command": "npx",\n "args": ["-y", "@davewind/mysql-mcp-server", "mysql://user:password@localhost:port/database"]\n }\n }\n} Notes
A Model Context Protocol (MCP) server for MySQL databases, written in JavaScript. It enables AI assistants like Cursor and n8n to execute SQL queries and interact with MySQL through the MCP standard. The server acts as a bridge between AI models and MySQL, allowing natural language database operations.
12 stars on GitHub. Last updated 2026-05-18. Licensed MIT.
Use cases
- Query MySQL databases from AI coding assistants like Cursor
- Integrate MySQL data retrieval into n8n AI workflows
- Build custom AI agents that can read and write to MySQL
Pros
- Lightweight JavaScript implementation easy to deploy
- Follows the MCP standard for interoperability with multiple AI tools
- Open source with permissive license
Cons
- Low community adoption (12 stars) suggests limited testing and support
- Minimal documentation beyond the repository README
- May lack production features like connection pooling or authentication
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Lightweight JavaScript implementation easy to deploy
- Follows the MCP standard for interoperability with multiple AI tools
- Open source with permissive license
Cons
- Low community adoption (12 stars) suggests limited testing and support
- Minimal documentation beyond the repository README
- May lack production features like connection pooling or authentication
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