search
Exact terms and meaning in one ranked pass. Hits carry the code with path:line ranges, so answers come straight from results.
Local code search for AI coding agents: a CLI and an MCP server over a ranked index that lives in plain files inside your repo. Hybrid keyword and semantic search, plus SQL relevance-ranked aggregation, so your agent answers questions about the codebase without reading it file by file. No accounts, no keys, no server.
One query, break this repo down by language, is about
6K tokens instead of about 140K reading files. Measured on real agent
runs, with a harness in the repo so you can reproduce it on your own.
Keyword search is live within seconds of indexing; semantic and hybrid ranking backfill in the background. Works in Claude Code, Cursor, and any MCP client.
Exact terms and meaning in one ranked pass. Hits carry the code with path:line ranges, so answers come straight from results.
Read-only SQL over the index. Search composes with GROUP BY, so "which files have the most code about X" is one query.
Incremental sync: only changed files re-chunk and re-embed. The server also auto-syncs in the background as queries arrive.
BM25 and vector rankings fuse in one pass, so a query works whether or not you know the exact identifier.
Rank and aggregate across the whole repo in one query, the kind of question file tools cannot express at any budget.
Embedding is a small local model, downloaded once. No accounts, no API keys, no server; code never leaves the machine.
Everything lives in .infino/ inside your repo: plain files you can copy, cache in CI, or gitignore. A live index, not a snapshot.