MCP server for read-only database intelligence: schema exploration, natural-language queries, EXPLAIN analysis, index suggestions. PostgreSQL / MySQL / SQLite. Zero LLM dependencies.. For remote mcp-
View on GitHub ↗Homepage ↗A Model Context Protocol server that lets an AI coding assistant explore, query, and audit a relational database without ever being able to write to it.
Point your MCP client at a database and ask questions in plain language. The client's LLM writes the SQL; this server parses it, refuses anything that is not a single read-only SELECT, executes it with a row cap, and returns structured results. Schema inspection, execution plans, index recommendations, and migration review come along with it.
The server makes no LLM API calls of its own, so there is no API key to configure — reasoning happens in whichever client you connect. Works with SQLite, PostgreSQL, and MySQL through SQLAlchemy.
Giving an assistant raw database credentials means one confused or prompt-injected turn can drop a table. Handing it a read-only replica loses schema context and plan analysis. This server takes the middle path: full introspection and query power, with mutation made structurally impossible at the parser level rather than by asking the model to behave.
The LLM lives in the client, not the server. Most NL-to-SQL designs put a model call inside the server; this one does not. The client already has a capable model, so the server ships zero LLM dependencies, zero API keys, and zero per-call inference cost — and stays usable from any MCP client, not just Claude.
That split defines the trust boundary: the SQL arriving at safety.py is model-authored and therefore untrusted, so it is parsed rather than pattern-matched, and a rejected query never reaches the driver.
From the project README.
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