Launched this week
grepai
grep for the AI era
74 followers
grep for the AI era
74 followers
grep was built in 1973. It finds text, not meaning. When you search for "authentication logic" but the code is named handleUserSession, grep fails. grepai uses vector embeddings to understand code semantically. Search by WHAT code does, not what it's called. Built for AI agents like Claude Code and Cursor, find relevant code instantly instead of browsing hundreds of files. Features: • Semantic search with natural language • Call graph tracing • 100% local • Real-time file watching
Hey Product Hunt! 👋
I'm Yoan, a French developer and YouTuber. I built grepai as an open-source side project, and my community absolutely crushed my expectations.
THE STORY: I challenged my YouTube community to help reach 300 GitHub stars. They didn't just meet it — they CRUSHED it with 750+ stars. A few days ago, I shared grepai on Reddit's r/ClaudeAI, and it hit 279k views. The response has been overwhelming.
THE PROBLEM: grep was built in 1973. It's amazing for exact text matching, but modern codebases need semantic understanding. When you want to find "authentication logic" but the code is named "handleUserSession," grep fails you. AI agents like Claude Code or Cursor spend massive amounts of tokens searching your codebase, often finding irrelevant results.
THE SOLUTION: grepai indexes your code using vector embeddings, enabling natural language queries. Search by WHAT code does, not what it's called. Plus: it reduces Claude Code input tokens by up to 80% (verified benchmark from my Reddit post).
WHAT MAKES IT SPECIAL:
- 🔒 Privacy-first: Runs 100% locally with Ollama
- ⚡ Real-time: Watches your files and auto-updates the index
- 🤖 AI-native: Built specifically for AI agent integration
- 📊 Call graph tracing: Find who calls a function instantly
It's completely free and open source. No cloud, no API keys required (unless you want OpenAI embeddings).
I'd love your honest feedback: What features would make grepai more useful for YOUR workflow? What's missing?
I'll be here all day answering every question. Merci! 🙏
Yoan
@yoandev Congrats on the launch, this deserves more upvotes. That 80% token reduction is a massive win for anyone using AI agents, and keeping it 100% local with Ollama is a huge plus. Very cool!!
@nick36_wu Thanks !
this is a really smart idea. search is definitely shifting toward ai , people are asking chatgpt and perplexity instead of googling. brands that don't show up in ai answers will lose out.
curious about the brand tracking , how does it work exactly? does it run queries periodically across chatgpt, claude, gemini and check if your brand appears? or is there another method? would love to understand the technical side.
@topfuelauto Thanks for the feedback! I think there is a slight misunderstanding regarding the nature of the tool.
GrepAI is actually a CLI tool for developers to query their local codebase. It acts like grep (the standard command line tool to find text in files), but instead of simple keyword matching, it uses vector embeddings (semantic search).
This allows you to search through your files by meaning and context, rather than exact strings. It is not a marketing tool to track brands on external platforms.
Cloudthread
Congrats! Can I use it in Cursor or only Claude Code?
@daniele_packard Thanks! Yes, you can definitely use it in Cursor. It works with pretty much all current tools.
I use it with Claude Code : Absolute Banger !
@numerogeek Love to hear that! 🚀 Glad it's working well with Claude Code.
very cool product @yoandev - I'm curious, can you help me understand how this differs from say setting up some sort of agent skills?
@justinchitla Think of Agent Skills as the Recipe (instructions on how to cook), and GrepAI as the Sous-Chef who instantly hands you the exact ingredients you need from a messy pantry.
Standard agents have to 'read' every label in the pantry (high token cost) to find things. GrepAI uses semantic search to find code by meaning (e.g., 'auth logic') instantly, drastically reducing context usage. It basically makes any agent/skill smarter and cheaper to run.
Congrats on the launch, Yoan! 🎉
As someone who uses Claude Code daily, this hits close to home. The frustration of searching for "authentication logic" and getting zero results because the function is called handleUserSession is so real.
The 80% token reduction claim is impressive — that alone could significantly cut costs for teams running AI agents at scale. And the fact that it runs 100% locally with Ollama is a huge plus for those of us working with sensitive codebases.
Quick question: how does grepai handle monorepos with multiple languages/frameworks? Does the semantic understanding work well across, say, a project mixing Python backend + TypeScript frontend?
Bookmarking this to test on my next coding session. The call graph tracing feature sounds particularly useful for onboarding onto unfamiliar codebases.
Bravo for keeping it open source! 👏
@mdnhtas Thanks a lot, really appreciate the kind words! 🙏
Regarding monorepos, I think the Workspace feature might be exactly what you are looking for: https://yoanbernabeu.github.io/grepai/workspace/
It allows you to define specific scopes/folders, which is perfect for managing mixed environments like Python/TS efficiently.