@Berkeley SkyLab, we’re the first to bring semantic search to Claude Code with a fully local index in a novel, lightweight structure — check it out at LEANN(https://github.com/yichuan-w/LEANN). Unlike Claude-context, which uploads all data to the cloud, or Serena, which is heavy and limited to keyword search, our solution installs in just 1 minute and instantly enhances Claude Code’s capabilities.Unlike Claude-context, which uploads everything to the cloud, and Serena, which is heavy and limited to keyword search, our method sets up in just 1 minute and instantly boosts Claude Code’s quality.

I think there’s huge potential for a fully local “Cursor-like” stack — no cloud, no API keys, just everything running on your machine.

The setup could be: • Cursor CLI for agentic/dev stuff (example:https://x.com/cursor_ai/status/1953559384531050724) • A local memory layer compatible with the CLI — something like LEANN (97% smaller index, zero cloud cost, full privacy, https://github.com/yichuan-w/LEANN) or Milvus (though Milvus often ends up cloud/token-based) • Your inference engine, e.g. Ollama, which is great for running OSS GPT models locally

With this, you’d have an offline, private, and blazing-fast personal dev+AI environment. LEANN in particular is built exactly for this kind of setup — tiny footprint, semantic search over your entire local world, and Claude Code/ Cursor –compatible out of the box, the ollama for generation. I guess this solution is not only free but also does not need any API.

But I do agree that this need some effort to set up, but maybe someone can make these easy and fully open-source

That's my vision, hope it can help. I think that if we combine all our personal data and organize it effectively, we can be 10 times more efficient. Long-term AI memory, all you speak and see will secretly be loaded to your own personal AI, and that can solve many difficulties, I think. https://x.com/YichuanM/status/1953886817906045211