How do I stop re-explaining project details to different AI models?

Your AI tools may keep their own history and memory without sharing context with each other. You open up a conversation in Claude, ChatGPT, or Cursor, and explain the project and conventions again. Vilix AI makes relevant saved context available across supported clients after you've connected them and configured the memory loop.

The actual cost of the blank-slate problem

It's not until you factor it all in that it stops feeling acceptable. A quick summary of your tech stack. The naming conventions you care about. The decision you made last week about the database schema structure. That this project targets Node 20 and your team avoids class components. You type this out once, twice, ten times, across ChatGPT, Claude, Cursor, and Codex and every time, they're saving a completely separate context.

You pay not just in keystrokes. Without the relevant project context, a conversation can produce answers shaped by generic assumptions. The AI suggests a pattern you already rejected, proposes a library you replaced three months ago, or asks a clarifying question you already answered in another tool yesterday. You fix it, move on, and repeat the cycle tomorrow.

Why the problem is structural, not a missing feature

A model request is executed using the context its application provides. Applications often have history, rules, and memory but it's usually scoped to their product. Claude Code has local auto memory, and Cursor has project rules. None of that, by default, creates a shared store across your various AI tools.

That shared layer is exactly what Vilix AI is. It provides a shared store at api.vilix.ai/mcp. Connect and authenticate each supported client, then configure its memory instructions so it can read and write to that store in your account.

How Vilix AI loads context automatically

Connect and authenticate each supported client, then add Vilix AI's custom instructions or configure its agent loop. The AI should call get_context with the latest message, use the returned context to compose its reply, call save_turn with the exact exchange, and then send the saved reply. Reuse chat_id within the conversation and verify both calls.

This means the context isn't in a system prompt that you have to remember to paste. It's not in a notes file that you open in a sidebar. It's in a server-side memory store tied to your Vilix AI account, where configured clients can retrieve relevant saved context.

A concrete example: Cursor to Claude without losing a beat

Say you spend a morning in Cursor working out an API route. You've told Vilix AI (via a Project and some saved memories) that this codebase uses Hono, targets Cloudflare Workers, and follows a specific error-handling pattern your team settled on in January. In this example, Cursor calls get_context with your message and retrieves those project details before composing its reply.

In the afternoon you switch over to Claude to think through a tricky edge case in that same route. You open a new conversation and ask about the edge case. In this example, the configured Claude client retrieves the saved project details and relevant Cursor exchange before replying. You can focus on the edge case without repeating the stack and conventions.

That's the scenario Vilix AI is built for. You can read more about how it works across tools in the cross-AI memory deep dive and in the companion post on avoiding copy-paste context workflows.

Setting up project context in Vilix AI

There are three places where project details live in Vilix AI:

• Projects and Tasks: a lightweight project manager whose state can be included in a get_context response. Create a project for the codebase, add tasks, and keep their status current so connected clients can retrieve the saved state.

• Saved memories: facts you want every tool to know about. Your stack, your conventions, a key architectural decision. You can save these by asking any connected AI to remember something, or directly in the Vilix AI dashboard.

• project_rules: short directives scoped to a specific project. Think of them like a standing system prompt for that codebase: "use TypeScript strict mode", "prefer functional components", "log errors to Sentry not console.error". Project rules can be returned in context for that project; the client still needs to retrieve and follow them.

Set it up once. From then on, any supported tool you connected to Vilix AI can retrieve relevant available context.

Which tools does Vilix AI support?

Supported clients need a compatible remote MCP connection and authentication. These include ChatGPT, Claude, Claude Code, Cursor, Codex, Grok, Manus, GitHub Copilot, Windsurf, Lovable, OpenClaw, and Hermes. Configure each client at api.vilix.ai/mcp using its supported setup path, then add the Vilix AI instructions and test retrieval and saving. No browser extension is required.

The result is that "start in Cursor, finish in Claude" is no longer a context reset.

Getting started

Vilix AI has a Free plan. The Pro plan ($19.99/month) includes a 7-day full trial so you can see the cross-tool memory working across your real projects before committing. Connect your first tool in a few minutes at the get-started page, then test a saved-context handoff between your tools.

Frequently asked questions

Does Vilix AI work with every AI tool I use?

Vilix AI works with clients that support a compatible remote MCP connection and authentication. Supported options include ChatGPT, Claude, Claude Code, Cursor, Codex, Grok, Manus, GitHub Copilot, Windsurf, Lovable, OpenClaw, and Hermes. Check the setup path for your client version and plan, then verify retrieval and saving.

How does Vilix AI know which project context to load?

When get_context runs, Vilix AI uses your message to retrieve relevant available context, which can include recent history, saved memories, related conversations, and project state. History and search features depend on your plan. Identify the relevant project when necessary to make the intended context clear.

What if I use Claude for some tasks and Cursor for others?

That's the exact use case Vilix AI is built for. Both configured clients can read from and write to the same memory store. After an exchange is successfully saved in Cursor, Claude can retrieve relevant details from it, and the same works in reverse.

Is my project context stored securely?

Yes. Context lives server-side in your Vilix AI account and is tied to your user identity, with saved exchanges retained in Vilix AI. Retrieved content can also appear in the connected tool's conversation and is subject to that provider's policies. You can review the details on the security page.

Do I need to be on a paid plan to use cross-tool memory?

The Free plan includes cross-tool memory. The Pro plan ($19.99/month, with a 7-day full trial) adds higher memory limits and additional features. Use the Free plan to test a saved-context handoff and decide whether you need the additional features.