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Tempreon is a personal memory layer for your AI tools, connected over MCP. Your knowledge, preferences, and decisions travel across Claude, ChatGPT, Cursor, and any MCP-capable client — captured once, available everywhere. It learns how you actually work instead of just storing what you said.
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Tempreon's answer:
Tempreon started with a simple observation: AI models keep changing, but the thing that makes them useful to you — your context, your preferences, your judgment — gets rebuilt from scratch inside every tool, and lost every time you move.
We built the layer that fixes that: person-owned memory served over the open Model Context Protocol, so it works across assistants instead of belonging to one. Along the way we open-sourced the pieces that are useful to everyone regardless of whether they use Tempreon — like memhaul, our MIT-licensed CLI for turning ChatGPT and Claude data exports into files you own.
The through-line is custody: the model is temporary, your memory shouldn't be.
Tempreon's answer:
Most alternatives in this space are memory infrastructure for developers building their own AI apps. If you're the person using several AI tools every day, that's not your problem — your problem is re-explaining yourself to each of them and losing everything when you switch.
The choice is really about who the memory is for. Ours is for you.
Tempreon's answer:
Tempreon is built for the person, not the app. Most memory products are developer APIs for adding memory to a single product; Tempreon is a memory layer you own that travels with you across every AI tool you use — Claude, ChatGPT, Cursor, anything MCP-capable.
Tempreon's answer:
Individuals who live in AI tools all day: operators, consultants, founders, sales professionals, and knowledge workers who use more than one assistant and are tired of being a stranger to each of them.
If you've ever pasted the same context into Claude and ChatGPT in the same week — you're the audience.
Tempreon's answer:
The protocol choice is the product decision: build on the open standard, and your memory works everywhere the standard does.
Based on our record, CodeMirror seems to be more popular. It has been mentiond 51 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
No syntax highlighting in the editor? I vibecoded a more robust browser Filesystem API based markdown editor last week. Recommend either rolling your own with a transparent textbox layered approach or just using Monaco or https://codemirror.net/. - Source: Hacker News / 4 days ago
The query editor in the Trigger.dev dashboard is built on CodeMirror 6 and uses a dual-parser architecture. - Source: dev.to / 6 months ago
CodeMirror – lighter than Monaco, still powerful. - Source: dev.to / 8 months ago
CodeMirror is amazing these days, super lightweight compared to Monaco, and pretty extensible: https://codemirror.net/ For something non-browser, I’m currently using Zed and it’s pretty good: https://zed.dev/. - Source: Hacker News / about 1 year ago
Scrappy co-creator here. Scrappy is local-first, so data is stored locally in your browser, and optionally replicated to a lightweight sync server, to help coordinate syncing between peers. In other words, Scrappy is almost entirely front-end. The only third-party dependencies are Yjs and CodeMirror . We don’t use any other libraries or frameworks like React. There’s no... - Source: Hacker News / about 1 year ago
ACE (Ajax Code Editor) - Focused and built towards coders, web designers, and web builders, ACE (Ajax Code Editor) can help...
ChainMemory - Portable, verifiable memory for AI agents — works across ChatGPT, Claude, Gemini and any MCP client
ProseMirror - A toolkit for building rich-text editors on the web
Memori - Persistent memory from agent trace, not just conversation
Monaco Editor - A browser based code editor
Mem0 - Your private, local memory layer for all AI tools
