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).
Thank you!
Right now Contextify parses the developer surfaces: Claude Code (including the Desktop "Code tab") and Codex.
Claude Cowork and Claude Desktop chat are on my radar. IIUC, they store local, plaintext transcripts, however the schema differs enough from Claude Code that it's a new parser.
I'm not totally clear on how the ChatGPT app will work. I believe it went through some major revisions recently, and it used to encrypt transcripts. I'll look at it more.
Which apps do you and your students use most?
I saw your comment about the AI Authenticity Audit. Focusing on their questioning, curating, editing, and iterating process is exactly the kind of thing Contextify is built to surface. I'm curious what format you had students submit it in?
If their tool were covered, the audit could be as simple as running Contextify and asking: "prepare a report showing the key turning points in pursuit of this insight: [some key passage]."