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I built a local archive for my AI chats because chat history isn't a knowledge base

A few months ago I caught myself doing something stupid. I had already worked through a problem with Claude, gotten a solid explanation, tweaked it in a follow-up thread — and a week later I was in ChatGPT asking the same question from s…

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A few months ago I caught myself doing something stupid.



I had already worked through a problem with Claude, gotten a solid explanation, tweaked it in a follow-up thread — and a week later I was in ChatGPT asking the same question from scratch.



Not because the old answer was wrong. Because I couldn't find it.






Learning changed. Memory didn't.



For a lot of day-to-day work — debugging, drafting, learning a new API, thinking through a design — my first stop is an AI chat now. Ask, push back, refine, land on something that fits my context.



That workflow is fast. Keeping it is not.



Chat history was built for the next message, not for next month:




  • Threads are siloed per tool (ChatGPT here, Claude there, Cursor somewhere else)

  • Search inside each app is thin

  • Exports end up as JSON files in a folder you never open again

  • Links to "that one great thread" rot in bookmarks



I didn't need another chat window. I needed a memory layer for conversations I already had.






What I tried first





  • ChatGPT / Claude history — fine for yesterday, bad for "what did I figure out in March?"


  • Notion / notes — manual copy-paste; always out of date


  • Raw export folders — data on disk, but no real search across threads and providers


  • Link lists — good for "where was that chat?" but not for full message text



So I built a tool to fix that.






ChatCabinet AI



ChatCabinet AI is a local-first desktop app (Electron + React + TypeScript) that turns scattered AI conversations into a searchable archive on your machine.



Rough flow:



Archive → Search → Knowledge → Personal AI





  1. Import chats from ChatGPT, Claude, Gemini, Cursor, JSON/Markdown/PDF/DOCX exports, or a folder scan


  2. Search full message text across everything — not just titles


  3. Organize with notes, tags, and collections


  4. Stay local — your archive lives under your control on disk



There's also a links layer (collections, tags, advanced search with operators like tag:, site:, platform:) for "never lose the URL." The conversation archive is the "have the text and search it" layer. Both can be backed up to a single JSON file.






Two problems, one app




















Layer Job
Links Bookmark chats, tag them, filter duplicates, find by domain/platform
Conversation archive Imported transcripts on disk, full-text search, copy messages, export to Obsidian


I'm not trying to replace your AI tools. I'm fixing what they leave behind.






Why local-first



Useful context shouldn't sit in someone else's cloud with search you don't control.



ChatCabinet keeps the archive on your computer. No cloud account required to run the app — your data stays on your machine.



If you've ever wanted to grep your past AI conversations — this is that energy, but with a UI.






Stack (for the curious)





  • Electron — desktop shell, filesystem access, userData for the archive


  • React + TypeScript — UI


  • On-disk storage for conversations; localStorage for the links layer

  • Import parsers for provider JSON, Cursor transcripts, Markdown, PDF, DOCX

  • Backup/restore as one JSON dump (full replace)



It's a focused desktop tool — built to do one job well: keep your AI conversations on your machine and make them easy to find again.






Get ChatCabinet



ChatCabinet AI is a ready-to-use desktop app for Windows.





Install, import your chats, and search across them in minutes.






Feedback



If you try ChatCabinet, I'd love to hear:




  1. Which AI tools you import from most often

  2. What search or organization feature saves you the most time

  3. What would make this your default archive for AI chats



Questions and ideas welcome in the comments.

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