I built this because AI coding assistants waste enormous amounts of context on code navigation. Every grep returns hundreds of
  text matches that the AI reads through — consuming 2000+ tokens for a simple "Where is function X?" question.

  AiDex pre-indexes your codebase with Tree-sitter and serves results via MCP (Model Context Protocol). A search returns ~50
  tokens instead of 2000+. It knows the difference between identifiers and text — searching for log won't match catalog.

  Technical stack: Tree-sitter for parsing, SQLite (WAL mode) for storage, MCP stdio transport. Supports 11 languages. Index time
  is ~1s per 1000 files, queries take 1-5ms.

  It's not a vector DB or embedding-based search — it's a plain identifier index with exact matches, prefix/substring search, and
  method signature extraction. Simple, fast, deterministic.

  Also includes a built-in task backlog (persisted in SQLite) and an interactive browser-based viewer for exploring the index.

  Works with Claude Code, Cursor, Windsurf, Gemini CLI, VS Code Copilot, and anything else that speaks MCP.