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Libro
The open-source brain for AI agents.
Most AI apps have goldfish memory. Libro fixes this. We are the first open-source User Context Layer that gives your AI agents infinite memory with zero pipeline changes. Just install the SDK, and your AI instantly remembers user preferences across sessions. Features include zero-cost local vectorization, automatic semantic chunking, and a Chrome Extension to build context passports anywhere on the web.
👋 Hey Product Hunt! I'm Lalit, the creator of Libro.
I love building AI tools, but I was incredibly frustrated by one thing: AI agents have goldfish memory.
Every time I started a new chat session with Claude or Cursor, I had to repeat the exact same context. "Use Tailwind," "Here is my database schema," "I prefer this coding style." I realized we needed a dedicated User Context Layer—an operating system for AI memory.
So, I built Libro.
Libro is an open-source, drop-in memory infrastructure layer for your AI applications. Instead of shoving massive system prompts into every API call, Libro sits quietly in the background: 🧠 Zero-cost Local Embeddings: We handle vectorization locally so you don't pay OpenAI per token. 🧩 Semantic Deduplication: As user preferences evolve, Libro automatically prunes outdated context. 🔌 Universal MCP Server: Plug Libro directly into Cursor, Windsurf, or Claude Desktop so your local AI instantly knows everything about you. 🌐 Chrome Extension: Extract context "passports" from any website or codebase with one click.
I built this because I wanted AI that actually remembers me. I've open-sourced the entire platform because I believe memory should belong to the user, not locked inside an LLM's black box.
I would absolutely love for you to try out the SDK, spin up the MCP server in your local editor, and let me know what you think! I'll be hanging out in the comments all day to answer any questions.
Cheers, Lalit
About Libro on Product Hunt
“The open-source brain for AI agents.”
Libro was submitted on Product Hunt and earned 11 upvotes and 1 comments, placing #57 on the daily leaderboard. Most AI apps have goldfish memory. Libro fixes this. We are the first open-source User Context Layer that gives your AI agents infinite memory with zero pipeline changes. Just install the SDK, and your AI instantly remembers user preferences across sessions. Features include zero-cost local vectorization, automatic semantic chunking, and a Chrome Extension to build context passports anywhere on the web.
On the analytics side, Libro competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Libro performed against the three products that launched closest to it on the same day.
Who hunted Libro?
Libro was hunted by Lalit Mohan Joshi. 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.
For a complete overview of Libro including community comment highlights and product details, visit the product overview.
Lalit Mohan Joshi