How is a cross-AI memory tool different from ChatGPT memory or Claude Projects?

ChatGPT memory is small, account-wide, and lives inside ChatGPT only, it doesn't travel to Claude or Cursor. Claude Projects pins documents and instructions to one workspace, but the workspace is scoped to Claude. A cross-AI memory tool lives above all the providers, so the same context is available regardless of which AI you open next.

Vilix connects to your AI tools through MCP (Model Context Protocol) with a one-time OAuth approval. Before each AI reply, Vilix reads the right past context automatically. After each reply, it saves the new exchange. There are no copy-paste steps and no per-message decisions to make. It also stores projects, tasks, and personal rules (user_rules) that any connected AI can read.

Does Vilix remember actual conversations or just facts about me?

It remembers the actual work. Most memory features store short distilled facts ('user lives in Colorado'). Vilix captures full conversations, your active project state (todo / doing / blocked / done), and your personal style preferences, then retrieves the most relevant pieces on demand. The memory grows with your work instead of snapshotting you.

Your memory is isolated per user. Data is encrypted in transit and at rest. Vilix does not sell user data and does not train third-party models on your private memory. You can export everything or delete it entirely at any time, with no waiting period.

How do I set up Vilix?

Sign up for the 7-day free trial, copy the MCP URL from your dashboard, paste it into your AI tool's connector settings, and approve OAuth. Setup takes under two minutes per tool. Note: custom MCP connectors require a desktop browser to set up, they don't work on phones yet.

Which AI tools does Vilix work with?

Vilix works with any AI tool that supports custom MCP connectors: Claude, ChatGPT, Cursor, Codex, GitHub Copilot, and Windsurf. Claude and ChatGPT both require a paid plan to enable custom MCP connectors; the others connect without that requirement. The Gemini app does not yet expose custom MCP connectors, a Google limitation, not a Vilix one.

May 27, 2026 · 9 min read

The best cross-AI memory tool: stop re-explaining yourself across ChatGPT, Claude, and Cursor

If you use more than one AI tool, you've felt it: ChatGPT forgets you the moment you open Claude, and Claude can't see what Cursor knows. A cross-AI memory tool is the layer that fixes it.

If you use only one AI assistant, you probably haven't noticed the problem yet. If you use more than one, ChatGPT for writing, Claude for code, Cursor inside the editor, Codex for terminal work, maybe Gemini when you're already in Workspace, you have. Every switch is a context reset. You re-explain your project to ChatGPT, then again to Claude, then again to Cursor. The more tools you use, the more time you burn re-briefing them on the same work.

The category that fixes this is called cross-AI memory. This post explains what cross-AI memory tools actually do, why ChatGPT's built-in memory and Claude Projects don't cover the same ground, and what to look for in a tool that carries your context across every AI you use.

What is a cross-AI memory tool?

A cross-AI memory tool is an independent layer that sits between you and your AI assistants. Instead of each provider keeping its own private store of facts about you, the cross-AI tool captures your work once and makes it available inside every connected AI. Three things have to be true for a tool to actually deserve the label:

It captures from any source. Whatever AI you used, ChatGPT, Claude, Cursor, Codex, anything else, the memory layer ingests from it.
Storage is provider-agnostic. Your facts, decisions, and preferences live independently of any one vendor, so switching tools or losing access to an account doesn't wipe your context.
It surfaces into any destination. Whichever AI you open next, relevant context is already there, no copy-paste, no manual hand-off.

The shorthand most people use for this is “one memory across every AI tool” or a “universal AI memory layer.” The technical shorthand is MCP, the Model Context Protocol that makes it possible for one memory backend to plug into many AI clients with a single one-time approval.

How is it different from ChatGPT memory or Claude Projects?

ChatGPT memory and Claude Projects both reduce repetition, but they're the wrong shape to solve the cross-tool case. We covered the side-by-side in detail in ChatGPT memory vs Claude Projects: what's the difference?. The short version:

ChatGPT memory is account-wide and ambient, a small set of facts the model decides to keep about you. It travels between chats inside ChatGPT and stops at the ChatGPT URL bar.
Claude Projects pins documents and instructions to one workspace. Inside that Project, Claude is grounded; outside it, the context evaporates.
Neither leaves its provider. ChatGPT memory cannot reach Claude. Claude Projects cannot reach Cursor. Both were designed as retention strategies for one company's product.

A cross-AI memory tool doesn't replace those features. Use them for what they cover well, single-tool continuity, project-scoped grounding inside one assistant, and add cross-tool memory on top for the case neither was built for.

How does Vilix work?

Vilix is a cross-AI memory layer. Three things happen, automatically, on every reply:

Before each AI reply, Vilix looks at your prompt and retrieves the most relevant past context, past conversations across tools, the active project's state, your personal preferences, and injects them.
After each reply, Vilix saves the new exchange so the next AI you open already has it.
Across every connected tool, the same memory is available. ChatGPT sees what Claude said yesterday. Cursor sees what ChatGPT decided this morning. Codex sees both.

Connecting is a one-time, one-click step: paste the Vilix MCP URL into your AI tool's connector settings, approve OAuth, done. There are no per-tool config files, no API tokens to manage, no per-message decisions to make. The retrieval and capture run in the background.

On top of conversation memory, Vilix gives every connected AI two extra layers of context, both auto-injected, no setup required after you fill them in once:

Projects & Tasks. A lightweight project manager. Create a project, add tasks with state (todo / doing / blocked / done) and priority, and the active project's full state shows up in every new chat. Any connected AI can read it and update it. See it on the features page.
user_rules. Personal style directives in plain English, “Short answers,” “No tables,” “Show code first.” Set them once and every connected AI applies them on every new chat.

What does it remember, facts about me, or actual work?

This is the deciding question between two design philosophies, and it's where most memory tools differ in practice.

Some tools scrape your profile once, your LinkedIn, your Notion, a one-time questionnaire, and serve back a static snapshot. That snapshot is true the day it's captured and quietly goes stale every day after. By the time it matters, your project has moved on and the memory hasn't.

Vilix is built the other way around. It captures the work as it happens: the actual conversations, the decisions inside them, the project state as it changes, the preferences you express in passing. Retrieval is relevance-ranked per query rather than a fixed bio, so the AI sees what matters for the question at hand. The memory grows with you instead of snapshotting you.

The practical test: ask any cross-AI memory tool, “What was I working on three days ago, and what's still open?” A facts-only memory can't answer. A work-aware memory can.

Is my data private?

Memory is intimate. The drafts, decisions, and half-formed ideas you trust an AI with belong to you. Privacy is a default in Vilix, not an upsell:

Your memory is isolated per user, no shared pools, no co-mingling.
Data is encrypted in transit and at rest.
Vilix does not sell user data, and does not train third-party models on your private memory.
You can export everything in a portable format, anytime.
You can delete individual memories or wipe your entire account instantly, with no waiting period.

For a deeper read on where memory should live and how to think about the trade-offs, see Local vs cloud AI memory.

How do I set it up?

The fast version, in order:

Start the 7-day free trial, no credit card required.
Copy your MCP URL from the dashboard.
Paste it into your AI tool's connector settings (see the setup docs for the exact path in each tool).
Approve OAuth. Done.

Two honest prereqs. First, custom MCP connectors require a desktop browser to add, you can't set them up from your phone yet, because the AI providers haven't exposed the connector UI on mobile. Once Vilix is connected on your laptop, your memory is available everywhere your account is, mobile included.

Second, Claude and ChatGPT only allow custom MCP connectors on their paid plans (Claude Pro, Max, Team, or Enterprise; ChatGPT Plus, Pro, or Business). ChatGPT also hides the custom-connector UI behind Developer Mode, which you toggle on under Settings → Apps & Connectors → Advanced settings. Cursor, GitHub Copilot, and Windsurf connect without a paid-tier requirement.

Which AI tools does it work with?

Today, Vilix connects to:

Claude (desktop & web; Pro / Max / Team / Enterprise)
ChatGPT (Plus / Pro / Business, with Developer Mode on)
Cursor
Codex
GitHub Copilot
Windsurf
Any other AI tool that supports custom MCP connectors

Notably absent: the Gemini app. Gemini doesn't yet expose custom MCP connectors, that's a Google limitation, not a Vilix one. The moment Gemini adds custom MCP support, Vilix will work there too with no extra work on your side. Until then, the easiest workaround is to keep your Gemini-side context in projects and let Vilix carry it across the other tools you use alongside it.

What good cross-AI memory feels like

The real test isn't a feature list. It's whether your AI tools stop feeling like strangers. A concrete sketch:

Monday morning, in ChatGPT on your phone, you brainstorm the architecture for a new billing flow. Tuesday afternoon, in Claude on your laptop, you ask it to draft the spec. Claude already has Monday's decisions, the trade-offs you considered, and the constraint you set on response latency, without you pasting a thing. Wednesday, in Cursor, you start implementing. Cursor knows the spec Claude wrote. Thursday, in ChatGPT again, you ask it to draft the launch email. It already knows what shipped.

That's the bar. Not “remembers your name.” Continuity across the actual work, across every tool, without any of the bookkeeping landing on you.

What to look for in a cross-AI memory tool

Captures full conversations, not just distilled facts. Facts-only memories are easy to ship and hard to live with.
MCP-native. Browser extensions break with every UI redesign; MCP is the actual standard providers are building toward.
One-click setup per tool. If you have to write config files or juggle API tokens per tool, the tool will lose to friction.
Source-aware retrieval. The memory should know which tool a thought came from, so context stays grounded and projects don't get crossed.
Export and delete, no waiting period. If you can't leave with your data, you shouldn't put it in.
No training on your private memory. Bare minimum, and not all tools say it explicitly.
Projects, tasks, and user_rules, not just chat memory. The work AIs need to see is bigger than a transcript.

Try it

If the cross-tool problem describes your day, the fix is a single connect-once step away. Start the 7-day Vilix free trial, every feature included, no credit card. If you don't upgrade, you keep a limited Free plan, and your data stays exportable.

Related reading: Why AI forgets conversations is the prequel to this post, why memory has to live outside any single model. Why cross-AI memory matters covers the compounding cost of context resets.