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.
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