This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Have you ever starred great open-source projects, then forgotten their names when you needed them? Starlens helps you find projects by semantics, tags, and context. It auto-summarizes READMEs with AI and auto-tags repos, making your Stars truly searchable. Supports Web dashboard, CLI, and AI tools like Claude Code via MCP protocol. Open-source GitHub Stars manager with natural language search, multi-level tags, and AI Q&A.
Starlens was born from my own frustration.
As a developer, I've starred thousands of repositories on GitHub — AI tools, frameworks, libraries, utility scripts. But when I actually needed to find one, I could only remember "it's a Python library for vector search," completely forgetting its name.
GitHub's native Stars list is just a chronologically sorted pile of links. After Astral shut down, this pain became even sharper. I tried manually organizing with note-taking apps, but the maintenance cost was too high and quickly became "organized ruins."
The core idea behind Starlens: let your Stars speak for themselves.
Instead of chasing perfect manual categorization, we use AI to automatically parse READMEs, generate semantic summaries, and apply intelligent tags. More importantly, through the MCP protocol, Claude Code, Codex, and other AI agents can directly access your collection — your Stars are no longer static bookmarks, but a dynamic knowledge base that AI can query.
From a simple search page to a complete ecosystem supporting Web工作台, CLI, and AI Agent integration, every step has been an iteration based on real usage scenarios.
If you've ever experienced the "star and forget" dilemma, give Starlens a try. I'd love to hear your feedback and suggestions!
Does the AI auto-tagging happen on the fly for newly starred repos, or do you have to trigger a re-sync to get the summaries and tags generated?
About Starlens on Product Hunt
“AI-powered semantic search for your GitHub Stars”
Starlens was submitted on Product Hunt and earned 0 upvotes and 2 comments, placing #146 on the daily leaderboard. Have you ever starred great open-source projects, then forgotten their names when you needed them? Starlens helps you find projects by semantics, tags, and context. It auto-summarizes READMEs with AI and auto-tags repos, making your Stars truly searchable. Supports Web dashboard, CLI, and AI tools like Claude Code via MCP protocol. Open-source GitHub Stars manager with natural language search, multi-level tags, and AI Q&A.
Starlens was featured in API (98.4k followers), Developer Tools (515.5k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 110.4k products, making this a competitive space to launch in.
Who hunted Starlens?
Starlens was hunted by YUANYANG WANG. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Starlens stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
YUANYANG WANG