AI Passport or AI Memory Layer: Which Actually Shares Context Between ChatGPT, Claude, and Other AI Tools?

Quick answer: "Share context between AI tools" is really two different problems wearing one name. If you want what your apps know about you, your preferences, your plans, to follow you from one assistant to another with your approval on every transfer, you want a permission-based data passport. Egoist Machines just shipped the consumer version of exactly that. If you want what you are working on, your decisions, your projects, your rules, the full record of your agent conversations, to be available to every tool and device, you want a shared memory layer that every tool reads and writes. Pick by what you need to carry: your personal data, or your work context.

The question hides two problems

Ask five people what "share context between ChatGPT, Claude, and other AI tools" means and you get two answers. One group means personal context: preferences, facts about their life, things they told one assistant that a different assistant should already know. The other group means working context: the decisions made yesterday, the state of a project, the instructions their agents follow, the full record of what was tried and what failed.

The products that answer the first question do not answer the second, and vice versa. Buying the wrong one fixes nothing.

The passport model: your data moves only when you say so

The passport model answers the personal-data question. The live consumer example is Egoist Machines, which launched its AI Passport in early October (press announcement October 7, 2026). The mechanics, from the announcement: connectors to 800 apps, covering ChatGPT, Claude, Gemini, Perplexity, plus Notion, Gmail, and wearables. When you add new information in a connected app, the detail lands in your Inbox; you review each item and decide whether other apps may use it, whether it stays in the original app, or whether it gets deleted. Connected apps can also request information about you, you set sensible defaults for accepting requests, and sensitive details such as dates of birth are never handed over without explicit permission. It is backed by Y Combinator and free to sign up for at ego.ist.

Read honestly, this is personal-data portability with a permission gate on every transfer. It answers "what do my apps know about me?" It does not store conversation records, project state, or agent work. If your world is scheduled agents that wake up blank every run, this is the wrong drawer.

The memory-layer model: one store every tool reads and writes

The memory-layer model answers the working-context question. Instead of moving data between apps with approval on each transfer, one store sits outside any single tool, and every tool reads from it and writes to it over MCP. The difference is operational: context is available by default, not by permission.

Two flavors exist. The self-run flavor is openIME (ioTus/openIME): a portable identity layer made of plain markdown files in a repository you own, organized as identity, memory, and exchange layers, so every connected tool reads from the same place and context flows between tools. Total ownership, no vendor, no subscription. The hosted flavor is Tabula: durable shared memory with a dashboard where you can see, edit, delete, export, or pause what each connected AI may access. The choice between them is about who runs the operation: you, or a service.

Where Vilix AI fits: the full record, zero infrastructure

For the memory-layer lane, Vilix AI is the pick when you need the full record, not just conclusions. It is cloud-hosted, so there is nothing to install or maintain. Point each AI tool at the same Vilix AI account over MCP, and what Claude learned yesterday is available to Codex today, on your laptop or your phone. The tools are get_context (recall) and save_turn (persist). What gets stored is the full user/assistant exchanges, plus derived memories, projects, tasks, personal rules, and reusable agent skills. Retrieval is semantic plus keyword, so an agent finds what it needs even when it asks differently than it was stored. Everything is exportable in a portable format, and you can delete individual memories or wipe the account instantly from the dashboard at app.vilix.ai. The free plan is free forever, and the 7-day Pro trial asks for no credit card. Learn how Vilix AI works.

The middle options

Not everyone needs either extreme. MemoryLake frames its product as a "universal memory passport": governed, versioned memory across sessions and models, closer to the memory layer, with governance as the selling point. Synapse is the manual, local option: an open-source browser extension that captures a full ChatGPT, Claude, or Gemini conversation into a portable capsule you carry into another tool yourself. And the free DIY version is the metaprompt: ask one AI to write a structured brief of everything a fresh session needs to know, review it, paste it into the next tool. You are the bridge, and the quality of the bridge is exactly the quality of the brief.

Which one answers the question?

Return to the question as asked. If "context" means your personal data and preferences, and you want to approve every transfer, get a passport. Egoist is the live consumer option. If "context" means your work, what your agents decided, what your projects look like, what rules they follow, get a memory layer, and choose it by how much of the operation you want to own: markdown files in a repo you control (openIME), a hosted dashboard you manage (Tabula), or a hosted service with zero infrastructure that keeps the full record (Vilix AI). The expensive mistake is buying the one that solves the other problem.

FAQ

Is an AI passport the same as AI memory? No. A passport moves personal data between apps with your permission on each transfer. A memory layer stores working context that connected tools read and write directly. Adjacent problems, different products.

Can both be used at once? In principle, yes. The passport handles what apps know about you; the memory layer handles what your agents are doing. Neither model forbids the other.

Do these options cover coding tools? Passport connectors target chat assistants and productivity apps. Memory layers over MCP target MCP clients such as Claude, Codex, Cursor, and OpenClaw. Match the product to where the work actually happens.

What should you check about privacy before committing? Who holds the store and what the export story is. Egoist's pitch is user ownership with per-request approval. For a memory layer, look for per-user data isolation, portable export, and instant delete before trusting it with real work.