I was tired of manual SQL introspection, so I built Legacy Lens (MCP Server)

We’ve all been there. You’re staring at a legacy database. 400 tables. Cryptic column names like FLG_Z_99 . No documentation. You try to explain it to an AI agent like Claude or Cursor, and it starts hallucinating JOINs that don’t exist. I was tired of copy-pasting DDL exports and manually explaining schemas. So, I built Legacy Lens . The Problem: The "Context Gap" AI models are smart, but they are "blind" to your local infrastructure. To make an LLM actually useful for database engineering, it needs more than just a connection string; it needs a semantic map of the data. In a world of "AI Wrappers," we often forget that the bottleneck isn't the AI's intelligence—it's the precision of the context we provide. The Solution: Model Context Protocol (MCP) I decided to leverage the Model Context Protocol . Instead of a simple wrapper, I built a dedicated introspection engine that acts as the AI's "eyes" inside the database. What Legacy Lens does: Deep Introspection: It doesn't just list tabl