How do I share context between ChatGPT, Claude, and other AI tools?

Short answer: today, they don't share anything by default. Each AI app keeps its own memory in its own silo, and moving context between them is manual unless you add a layer that sits outside all of them. Your options, from simplest to most complete: copy-paste, shared notes files, an MCP memory server, or a hosted shared-memory layer like Vilix AI.

Why don't they just share?

Because each one is a walled garden. OpenAI's help center is explicit that ChatGPT memory draws only on ChatGPT-internal sources: past chats, saved memories, custom instructions, library files. "Chats can reference other conversations in the same project, but they cannot reference conversations outside the project." And that's inside one product. Nothing crosses to Claude.

Anthropic's side is the same story: "Each project has its own separate memory space... separate from other projects or non-project chats." Claude Code's docs note that "each Claude Code session begins with a fresh context window." Researchers studying the problem put it bluntly: "A conversation with Claude will never be seen by ChatGPT, and vice versa, unless you manually copy and paste it in there." Memory is "trapped in a silo, living with the application where it was accumulated."

This is the part people trip over: ChatGPT's memory feature and Claude's memory feature are real, and neither one helps the other app. If you use both, you brief both. Every time. The underlying mechanism, why models can't remember between sessions at all, is covered in why AI agents forget everything between sessions.

What people actually do today

Copy-paste between apps. The universal workaround. Download or copy from one assistant, paste into the other. It works for one-off handoffs and falls apart fast: every handoff makes a copy, no copy knows about the others, and after two or three hops there's no reliable answer to which version is current. One guide calls this "the copy problem": context doesn't travel, so each assistant sees a document with no history. Formatting degrades along the way.

Shared markdown notes. Plenty of developers keep one markdown file (or a Notion doc) that they paste context into and tell each tool to read. On Hacker News, one workflow that came up repeatedly is a single markdown file that both Claude Code and Codex are told to keep updated. It works until someone forgets to update it, which is always.

CLAUDE.md and friends. Claude Code auto-loads CLAUDE.md files each session; Cursor has its cursor rules; Gemini has its own equivalent. These are good for project instructions, but they're per-tool files that don't talk to each other. Static instructions, not shared memory.

Claude's one-time import. Claude's settings offer a memory import: you paste an extraction prompt into ChatGPT, paste the output back. It's a frozen one-time snapshot, marked experimental, and it doesn't include conversation history. Fine for a first date, not a relationship.

An MCP memory server. The Model Context Protocol is the open standard for connecting AI apps to external systems, and its official reference servers include a knowledge-graph memory server you can run with npx -y @modelcontextprotocol/server-memory and wire into any MCP client. This is the closest thing to a standard answer, and it's genuinely useful for explicit memories you choose to store. The limit: no surveyed memory MCP server can read the apps' own memory profiles or chat history. It stores what you tell it to store.

The complete option: one memory outside all of them

The workarounds above all share a flaw: the human is the sync layer. The fix is a memory store that every tool connects to, so no one has to carry context between apps by hand.

Vilix AI works this way: you connect each AI client, Claude, Codex, Cursor, ChatGPT, OpenClaw, Hermes, and others, to the same Vilix AI account over MCP. Each tool gets memory tools that save and retrieve from the one shared store. Tell Claude your deployment checklist once; Codex sees it. Retrieval is semantic plus keyword, so it finds what you meant and matches exact strings like order IDs and policy names literally. When two tools save conflicting facts, the newest write wins, and since every tool reads the same store, you only ever correct something in one place.

Vilix AI is a hosted service, so there's no server to run. Each tool connects to your Vilix AI account over MCP in its own quick setup step, and from then on every connected tool reads and writes the same shared memory.

FAQ

Can ChatGPT read my Claude conversations? No. There is no integration between them. Anything you want in both places, you move yourself or route through a shared layer.

Does MCP solve this on its own? MCP is the plumbing, not the memory. It standardizes how apps talk to external systems, which is what makes a shared memory server possible. You still need the memory server itself.

What about just using one AI for everything? If one tool covered all your work, the problem would vanish. In practice, as one Hacker News commenter put it: "I use Claude for some tasks, Cursor for coding, ChatGPT for research, and Perplexity for quick lookups. The problem is none of them know what I've discussed with the others." That's exactly the setup where silos hurt most.

Is my data portable if I stop? With Vilix AI, yes: you can export all of your memory in a portable format anytime, delete individual memories, or wipe the account instantly.

The bottom line

Every AI app remembers you a little, and none of them remember you to each other. Until that changes at the platform level, your realistic options are manual handoffs, disciplined notes files, a self-hosted MCP memory server, or a shared layer like Vilix AI that makes every connected tool read from the same memory. For a head-to-head of the memory tools, see what are the best AI memory tools. Pick based on how much manual syncing you're willing to keep doing.