AI agents already write database schemas. Ask Claude or Cursor for a feature and the migration file comes back with tables, columns, and foreign keys — named however the model's training data leans that day. user_id here, userId there, usr_no when it read one too many legacy dumps. The agent isn't wrong; it just has no idea your team writes cust_no, because your naming convention lives in a wiki the model has never seen.
That's the actual problem an ERD MCP server solves. Not "AI can draw diagrams now" — but that schema work done by agents can follow the same standard as schema work done by people. This post explains what sqemo-mcp does, how the naming part works, and — in the same honest-comparison spirit as our dbdiagram comparison — what it doesn't do yet.
What an MCP server is, in one paragraph
MCP (Model Context Protocol) is the open standard for giving AI agents tools. A server exposes typed operations — "list entities," "add an attribute," "export SQL" — and any MCP-capable client (Claude Code, Claude Desktop, Cursor, Codex, and a growing list) can call them. Instead of the agent hallucinating your schema from half-remembered context, it reads the real one and edits it through operations that enforce your rules.
