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Comment by bredren

13 hours ago

I've been working on Contextify, which backs up your Claude Code and Codex conversational history and makes your entire history available via a skill or mcp.

Contextify (https://contextify.sh)

It is very flexible, you use it the normal flow of CLI AI conversations:

   1. Resume unfinished work → "where did we leave off on that?"
   2. Recover the intent/scope → "what was the actual goal of this whole effort?"
   3. Verify it got done → "did we ever finish that, and which session proves it?"
   4. Recall a fix → "how did we fix this the last time it broke?"
   5. Reconstruct a decision → "why did we go this way instead of the other one?"
   6. Branch/PR archaeology → "what was this branch even for?"
   7. Recall a plan → "what was the plan we landed on for that?"
   8. Activity over a window → "what did I ship or close in the last few days?"

Just add "use total recall" or invoke the skill directly via /total-recall or $total-recall.

You can self-host your database to keep it local and sync your history across multiple computers. The local server is source available under FSL-1.1-Apache-2.0.

There are macos and linux clients, and I'm pretty close on a windows client. All share a common Swift-based core.

Great work! Love the harnessing of Apple's local inference. Wondering if you'd be willing to support the same conversational export, summarization, and search/retrieval flows but for the consumer platforms (ChatGPT and Claude) that have local conversations stored? (e.g. I've seen that local Claude Cowork conversations are stored in some kind of JSON-based schema that might be similar to Claude Code, but I'm really not too sure).