Original Summary

AI agents forget everything between sessions. You re-explain the repo, the conventions, the approach that already failed — every single time. I built CogniCore to fix that, and it's live on Product Hunt today. It's an open-source memory layer that runs as an MCP server, so the memory follows you across Claude, ChatGPT, Cursor and Claude Code rather than being locked inside one app. MIT licensed, no vector database, no embedding server. What's actually real, and all of it verifiable: Live hosted service at mcp.cognicoree.tech, with GitHub sign-in On PyPI as cognicore-env — 13,000+ downloads since April 2026 Listed in the official MCP Registry Independently scanned and graded A (95/100) for safety by mcp.market 275 public commits, 77 stars Honest limits. Retrieval is TF-IDF/BM25 running in-process. On LongMemEval multihop, strict recall@5 goes 78.8% → 85.2% at a 5-chunk window and 87.2% → 92.8% at 10 — at 20 chunks the baseline catches up, and we report that rather than hiding it. And the recall output doesn't yet expose provenance, which is the next thing I'd fix. Built by three final-year students in Mumbai. https://www.producthunt.com/products/cognicore If context loss is something you fight with, I'd like your read on it — criticism is more useful to us than a kind word.   submitted by   /u/Neither-Witness-6010 [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/10/19 16:21:31