MySQL MCP Server

The @davewind/mysql-mcp-server is a lightweight Model Context Protocol (MCP) server that gives large‑language models (LLMs) secure, read‑only access to MySQL databases. By exposing only schema information and SELECT queries, it removes the risk of accidental data modification while still allowing an AI assistant to perform ad‑hoc analytics, answer schema questions, or generate data‑driven insights. This makes it ideal for developers who want to integrate database knowledge into conversational agents without exposing full database privileges.

At its core, the server listens for MCP‑compliant JSON-RPC messages over standard input and output. When an LLM requests a tool invocation, the server validates that the supplied SQL contains only SELECT statements and then runs it inside a READ ONLY transaction. The results are returned as structured JSON, preserving type information and allowing downstream tooling to render tables or charts. Schema discovery is performed automatically on startup, providing a catalog of tables with column names and data types that can be queried by the assistant to understand the database layout.

Key capabilities include:

• Read‑only enforcement: All SQL is vetted and executed within a transaction that prevents any write or schema‑altering commands.
• Schema exposure: The server publishes a JSON representation of each table’s structure, enabling the LLM to ask questions like “What columns does have?” without direct database access.
• Tool integration: A single tool named query accepts raw SQL strings, making it trivial to embed into an LLM’s prompt chain.
• MCP compliance: The implementation follows the MCP specification exactly, ensuring compatibility with any LLM or orchestration system that supports the protocol.

Typical use cases include building data‑aware chatbots for internal knowledge bases, generating dynamic reports from live data, or enabling AI‑powered analytics dashboards that can answer natural‑language questions about sales figures, inventory levels, or customer behavior. Developers can hook the server into existing LLM workflows by adding a command entry to their MCP configuration file, after which the assistant can seamlessly invoke database queries as part of a conversation.

Because the server operates over JSON‑RPC and enforces strict read‑only rules, it can be deployed in environments with tight security requirements—such as regulated industries or production systems where accidental writes could cause serious issues. Its minimal configuration and zero‑dependency design make it straightforward to add to existing MCP ecosystems, providing a powerful bridge between conversational AI and structured data without compromising safety.