MySQL Query MCP Server

The MySQL Query MCP Server is a lightweight, read‑only bridge that lets AI assistants such as Claude or Cursor IDE interrogate MySQL databases directly through the Model Context Protocol. By exposing a controlled set of SQL commands—SELECT, SHOW, and DESCRIBE—it enables developers to explore data structures, retrieve sample rows, and inspect metadata without risking accidental writes or schema changes. This focus on safety makes it ideal for debugging, data validation, and rapid prototyping where the AI can ask questions like “What columns exist in users?” or “Show me a few rows from orders.”

At its core, the server manages multiple pre‑configured environments (local, development, staging, production) through environment variables. It supports SSL connections and configurable timeouts to keep queries fast and secure, while rejecting any write operations by design. The API surface is intentionally minimal: list available environments, fetch database metadata, and execute arbitrary read‑only queries. This simplicity reduces surface area for attack and makes the server easy to audit.

For developers, the value lies in seamless integration with existing MCP‑compatible tools. Once the server is running, any tool that can send MCP requests—whether a web IDE, a command‑line client, or an AI chatbot—can request schema details or run exploratory queries without leaving the assistant’s context. This tight coupling eliminates the need to switch between a database client and the AI interface, streamlining data‑driven workflows.

Real‑world scenarios include troubleshooting production issues by letting the assistant query logs or configuration tables, validating data models before code changes, and teaching new team members by walking through live queries. Because the server never allows data modification, it can be safely deployed in shared or production environments where write access is restricted.

Unique advantages of this MCP server are its strict read‑only enforcement, environment abstraction, and built‑in SSL support—all wrapped in a minimal command‑line binary. These features give teams confidence that the AI can interrogate databases safely while still delivering rich, contextual insights directly within their preferred development tools.