Semantically searches markdown documentation within code repositories, leveraging embeddings for AI-assisted information retrieval.
KB provides a specialized embeddings-based search system designed to efficiently navigate markdown documentation across various code repositories. It enables users, particularly those working with AI coding assistants like Claude or Cursor, to find relevant information based on meaning rather than just keywords. By intelligently chunking markdown and generating semantic embeddings, KB transforms raw documentation into a powerful, searchable knowledge base, making it easier to access critical project details and accelerate development workflows.