Smarter AI Development Workflows
Replen Smarter AI Development Workflows A local intelligence layer for AI coding agents.
Website · Docs · Install · Workflow · MCP · Skill · Self-host · Research · app.replen.dev
Claude Code, Codex and Cursor already help inside the repo you are working on. Replen gives them a local intelligence layer across every repo you build.
It maps each project to what it actually does, building an ontology and knowledge graph of your portfolio: computer vision, geospatial analysis, market-making, scraping, workflow automation, or whatever else you build. It then watches the OSS frontier and continuously scores relevant projects against your real capabilities, using semantic matching and a self-tuning learning loop shaped by what you adopt, skip and review.
The result is not a trending list, a keyword search, or a static repo graph. Replen autonomously surfaces a small number of high-signal suggestions your AI coding tools can actually use.
Sometimes that means adopting a library as-is. Sometimes it means porting a function or algorithm from a larger project. Sometimes it means cherry-picking a technique, or clean-room building an idea from scratch to stay licence-compliant.
The judgement happens locally, inside your session, against your real code. Your code never leaves your machine.
Replen aims for a few useful suggestions a month. Most days it says nothing. When something real lands, your AI tool can mention it the next time you open the repo, as a short note at the end of its first reply:
From the project README.
Add the radar badge to your README — it shows your project was picked up by MCP Radar and links to this page:
[](https://mcp.liqiwa.com/s/replenhq--replen.html)
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