Can AI remember across different tools (ChatGPT, Claude, Perplexity, Cursor)?

Natively, no AI tool remembers what you said in another. Here is why the providers are siloed, and how a memory layer above them gives ChatGPT, Claude, Perplexity, and Cursor shared context.

No. AI does not remember across different tools natively. ChatGPT, Claude, Perplexity, and Cursor are built by separate companies on separate infrastructure, and none of them can read what you said in another. Each provider's memory, where it exists at all, is locked inside that provider. The only way to get genuine cross-tool memory today is to add a memory layer that sits above all of them and feeds context into whichever tool you open.

That answer surprises people, because the tools feel similar enough that continuity seems like it should be free. It isn't. Understanding why it isn't tells you exactly what to do instead.

Why can't ChatGPT see my Claude conversations?

Because there is no shared place for that context to live. A conversation you have in Claude is stored by Anthropic, in Anthropic's account system, retrievable only by Anthropic's product. ChatGPT has no API into that, no permission to read it, and no commercial reason to build one. The same is true in reverse, and for Perplexity and Cursor too.

Underneath, the models themselves are stateless. As covered in Why AI forgets conversations, a language model has no memory between requests. The sense of continuity inside a single chat is the application re-sending earlier messages with every new prompt. That trick only works within one tool's own conversation store. Cross the boundary to another vendor and there is nothing to re-send.

Don't built-in memory features solve this?

They solve part of it, within one tool. ChatGPT's memory, Claude's project knowledge, and similar features genuinely help when you stay inside that one product. They have three structural limits when you don't:

• They are provider-bound. ChatGPT memory never reaches Claude or Cursor. It was never designed to.
• They are usually narrow. A handful of remembered facts, not a project's worth of decisions, constraints, and history.
• They are often opaque. You cannot always see what was stored, in what shape, or how it gets retrieved.

So built-in memory is real and worth using. It just answers the easy single-tool question, not the harder cross-tool one most real workflows run into.

What does cross-tool AI memory actually require?

For one tool to act on what you told another, the context has to live somewhere neutral — outside any single provider — and be reachable from all of them. In practice that means three capabilities:

• Provider-agnostic capture. Whatever tool you used, the relevant decisions and facts get recorded into a shared store.
• Independent storage. Memory is held separately from any AI vendor so switching tools does not lose it.
• Retrieval into any destination. When you open the next tool, the most relevant context is fetched and put into the prompt.

The model still has no inherent memory. Every prompt is simply seeded with the right prior context automatically. From your seat it looks like the AI remembered, even though, mechanically, it never did.

How is a memory layer connected to all these tools?

The practical mechanism is the Model Context Protocol, an open standard for connecting AI tools to external context sources. A growing set of clients — Claude, Cursor, and others — speak MCP, which means a single MCP-based memory server can serve all of them through one connection rather than a bespoke integration per tool. The background is in What is MCP (Model Context Protocol).

This is the approach Vilix takes. It is a persistent memory layer across ChatGPT, Claude, Cursor, Perplexity, Gemini, and any MCP-compatible tool, connected once via OAuth. It captures full conversation context with semantic and source-aware retrieval, and you can export or delete everything at any time. Vilix is not the only way to build this, but it is a working example of the layer-above-providers design.

A concrete walkthrough

Say you research a vendor comparison in Perplexity on Monday, make the architecture call with Claude on Tuesday, and start implementing in Cursor on Wednesday. Natively, Wednesday's editor knows nothing about Monday's research or Tuesday's decision. You re-paste, re-summarise, and hope you didn't drop a constraint.

With a memory layer in front of all three, Tuesday's session already has Monday's findings, and Wednesday's Cursor session already has the decision and its reasoning. The tools behave like one collaborator with a continuous memory instead of three strangers.

Frequently asked questions

Does Claude remember ChatGPT conversations?

No. Claude and ChatGPT are separate products from separate companies with no shared storage. Claude cannot read ChatGPT history, and vice versa, unless an external memory layer carries that context between them.

Can Cursor access my ChatGPT or Claude memory?

Not natively. Cursor keeps its own workspace context and cannot reach into other vendors' memory. An MCP-connected memory server can supply shared context to Cursor and the others alike.

Will providers eventually make memory portable themselves?

It is unlikely to be a priority, since portable memory reduces lock-in for each vendor. A neutral layer is the more probable path, which is the argument in Why cross-AI memory matters.

Is cross-tool memory just pasting a brief into each tool?

Manual briefs are a crude version of the same idea and they do work. The difference is automation and retrieval: a memory layer surfaces the relevant context without you maintaining and re-pasting a document every session.

Do I have to give a memory layer all my chat data?

You should expect to control what is captured and to be able to inspect, export, and delete it. Memory you cannot audit is memory you should not trust.

The short version

AI cannot remember across tools on its own, and the providers are not incentivised to fix that for you. The realistic answer is to own the memory layer yourself or use one built for the job. If a shared memory across your AI tools is what you want, you can try Vilix free for 7 days and see whether the cross-tool continuity holds up in your own workflow.