How do I avoid copy-pasting context between different AI chat interfaces?

Connect and authenticate Vilix AI in each of your supported tools and add the custom instructions. The client can retrieve relevant saved context, compose its reply, save the exact exchange, and return the saved reply. That makes earlier work available when you switch tools without needing to transfer all details manually.

Why context gets lost between AI tools

Many AI apps preserve their own chat history or native memory. The gap is visible when you switch products; what ChatGPT remembers is not automatically available to Cursor, and a decision saved in Claude may be missing from another assistant's context. Closing a browser tab does not erase the history, but each product maintains its own.

A common manual workaround is to keep a running notes file, paste the relevant chunk into each new chat, and hope you remembered the part the AI actually needs. It works, but it is friction that mounts. The longer a project runs, the more context there is to carry, and the more painful each switch is.

What Vilix AI does differently

Vilix AI is an MCP-native persistent memory layer. You connect it once per tool by adding a custom MCP connector which points to api.vilix.ai/mcp. After authentication, you add the Vilix AI custom instructions and verify this sequence in a real conversation:

• Before the reply, the AI calls get_context, which loads your recent messages, your saved memories from past conversations, any rules you have set (such as "always use TypeScript strict mode"), and the live state of any active projects and tasks.

• After composing the reply, the AI calls save_turn with the exact exchange, and then returns the saved reply and reuses chat_id within the same conversation.

Memory is stored server-side in your Vilix AI account, tied to you and not any one tool or device. That is what makes the cross-tool handoff work without any manual step on your part.

You can read more about how this works on the cross-AI memory page, or see the pattern in context in the post on cross-AI memory in practice.

A concrete example: Cursor to Claude handoff

Say you spend an hour in Cursor working through a tricky refactor in your API layer. You end up deciding that the auth middleware needs to move, but you want to think through the implications before writing the code. You open Claude to talk it through.

Without Vilix AI, that conversation in Claude starts cold. You paste in the relevant file, explain the current structure, describe the plan you formed in Cursor, and ask your question. You have just spent five minutes reconstructing context that already existed.

With Vilix AI connected in both tools, Claude calls get_context before replying. It uses the recent Cursor exchanges where you discussed the middleware plan, plus the notes Vilix AI has saved about your API conventions. By the time Claude responds, it knows what you are working on. You skip straight to the architectural question.

Before sending each reply, Claude calls save_turn to persist the exchange. You go back to Cursor for implementation. Cursor can retrieve the saved conclusions on its next context request.

For a detailed walkthrough of this specific pattern, see the post on keeping context between Claude and Cursor.

What gets retrieved and how

Vilix AI supports semantic and keyword search over stored turns; history and retrieval tools depend on your plan. When you start a new conversation, it shows you the most relevant prior exchanges, not just the most recent. If you worked on authentication three weeks ago and today's question is about auth, relevant older turns can show even after other conversations.

Three types of stored content contribute to each context load:

• Conversation turns: what you and each AI said, stored per turn and searchable by topic.

• User rules: short personal directives you set once ("short answers", "always show the full function, not a snippet") that are included in retrieved context for connected tools to apply.

• Projects and tasks: a lightweight project manager whose current state auto-injects into context so the AI knows what you are building and where it stands.

Which tools work with Vilix AI

Any tool which supports a custom MCP connector can use Vilix AI. The ones where the pattern is most useful daily are ChatGPT, Claude, Claude Code, Cursor, Codex, Grok, Manus, GitHub Copilot, Windsurf, and Lovable. You add the same connector endpoint in each tool and they all read from and write to the same memory store in your account.

There is no browser extension to manage, and no sidebar. The memory moves because the protocol moves it.

Getting started

Vilix AI has a free tier and a Pro plan at $19.99 per month with a 7-day full-Pro trial. Setup is one custom MCP connector per tool you want to connect. Start with one tool and verify retrieval and saving before connecting the rest.

If you are tired of rebuilding context every time you switch tabs, try Vilix AI free and see how much repeated explanation you can avoid.

Frequently asked questions

Does Vilix AI work if I use different AI tools for different tasks?

Yes. That's exactly what Vilix AI is built for. Connect and authenticate it in each tool, then add the Vilix AI instructions so the clients retrieve and save context as they work. You can use Claude for reasoning, Cursor for coding, and ChatGPT for writing, and all three can retrieve relevant saved context from your Vilix AI account.

Do I have to do anything to trigger the context retrieval?

Install the Vilix AI custom instructions after connecting each client, or wire the calls into your agent loop. The instructions tell the AI to retrieve context and save the completed exchange before returning its reply. Verify both calls; registering the server alone does not ensure that the client invokes them.

What happens if I start a conversation on one device and continue on another?

Memory is stored server-side in your Vilix AI account. A supported client connected to that account can retrieve relevant saved context on another device. You may need to configure the client on the new machine, but there is no memory file to transfer.

How does Vilix AI decide which past context to load?

Vilix AI uses both semantic search and keyword search over your stored turns to find what is most relevant to the current conversation. Recent messages are available, and older conversations can surface when they are topically related to what you are asking now.

Is there a limit to how much context Vilix AI can store?

Storage limits depend on your plan. The free tier covers everyday use for a single developer. The Pro and Power plans support heavier usage; see the current pricing page for retrieval features and project limits.