Sense, code intelligence for AI agents
Your AI has your code's text, never its map. Fix that.
What it does
Your AI coding agent reads 19 files to answer "who calls this?" because it has your code's text but never its map. Sense indexes your repo once and serves your AI a symbol graph, blast radius, semantic search, and convention detection over MCP. It finishes the same task in half the tool calls and ~32% fewer tokens, with better correctness. One local Go binary. No API key, no cloud, no Python. Works with Claude Code, Cursor, Codex, and OpenCode. Free and open source.
Does the same job
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hi guys. been working on something i think is fundamentally missing in today's workflow with ai agents. vcs. i find myself struggling with questions that agents can't answer like "why did you do it?", "when did u delete this folder? why?", etc. or trying to /rewind (after a /compact...) or basically `bisect` to find when and why something was done by the agent in the current / previous session. just like git did for code, i think we are the same core capabilities with ai agents so... i developed an open source solution for that (currently supporting claude code) would love to…
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I built this because I got tired of watching Claude Code read through massive files just to find a few functions. Sourcerer lets AI agents search code semantically and grab exactly the code chunks they need instead of burning tokens on whole files. It uses tree-sitter to parse your codebase and creates a searchable index. So instead of "read auth.py (538 lines)", an agent can search for "user authentication logic" and get back just the relevant functions. Demo: https://asciinema.org/a/736638 GitHub: https://github.com/st3v3nmw/sourcerer-mcp
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