An MCP server that inspects AI-generated code and returns a deterministic list of structural and safety violations, so an AI coding agent can fix its own output before the code lands.
MCP server that gives coding agents persistent, verified memory of codebase decisions, conventions, and skills, with evidence-based claims that are re-checked via git hooks and human-gated review. Enables memory search, propose/approve, chat harvesting, and critique across MCP-compatible tools.
Local memory MCP server that survives context compaction, learns from errors, injects fixes before the next attempt, and syncs to your git repo so your whole team shares it.