Claude Code and Cursor: One Shared Context
Two MCP-native coding agents, one shared vault
You use Claude Code in the terminal for some work and Cursor in the editor for the rest. Both are sharp. Neither knows what you did in the other. You set up your stack, your conventions, and your constraints in one — then open the other and start over.
They're both built on MCP. That's the detail that fixes this.
Do Claude Code and Cursor share context?
No — not on their own. Claude Code maintains context within a session and carries project instructions forward through CLAUDE.md. Cursor does the same through its own rules files and indexed workspace. Each is scoped to its own tool. Nothing you establish in one crosses to the other.
This isn't an oversight. Every AI tool builds its own memory of you because that stored context is what keeps you inside the product — the more it knows, the higher the cost of leaving. The result for anyone using two tools is duplicated setup and context that drifts out of sync the moment you update one and forget the other.
And most developers do use more than one. According to Stack Overflow's 2025 Developer Survey, 84% of developers use or plan to use AI tools in their workflow — and the people reaching for a terminal agent and an editor agent are squarely in that group.
What actually works — one shared layer both connect to
The fix is to stop storing your context inside either tool and put it in a layer both connect to. Because Claude Code and Cursor are both MCP clients, this is the cleanest possible pair — no exports, no copy-paste, no bridge to maintain.
Here's the loop. Your identity, stack, conventions, and current priorities live in one vault. Claude Code loads that context over MCP at the start of a session. You work out an architecture decision, refine a convention, or lock a constraint — and save it back to the vault in the same session. Open Cursor later and it reads the same vault, decision included.
The write-back is what closes the loop. A shared layer that only feeds both tools still leaves you updating it by hand. One that both reads and writes means the tools maintain your context as you work. And with a custom instruction telling the agent to save decisions back at the end of a session, that capture runs automatically instead of relying on you to remember.
The distinction worth holding onto: this is shared context, not merged sessions. Claude Code and Cursor still run independently — you're not piping one's conversation into the other. What they share is the durable picture of who you are and what you're building, so neither starts cold.
How to set it up
Connect both tools to one context layer over MCP. In practice:
- Put your context in a vault both tools can reach. Not in
CLAUDE.mdand not in Cursor's rules — those are per-tool. A dedicated layer like Unabyss holds your identity, stack, and current work in one structured place, extracted from your real sources so it starts accurate instead of blank. - Connect Claude Code over MCP. Point it at the Unabyss MCP server in your config. It loads your context at session start — before you type.
- Connect Cursor over MCP. Same server, same context. Cursor now reads the identical picture Claude Code does.
- Turn on save-back. Add a custom instruction telling each agent to save decisions and new context to the vault as you work. That's what makes a decision in Claude Code show up in Cursor without you moving anything.
Project-specific files still earn their place — keep CLAUDE.md for build commands and repo conventions that belong to the codebase. The shared layer handles what's true across both tools and every project: who you are, how you work, what you're focused on now.
For the full multi-tool version of this setup, see How to Share Memory Across All Your AI Tools. For tightening Claude Code specifically, How to Optimize Context in Claude Code covers keeping that context lean.
The short version
Claude Code and Cursor don't share context on their own, and they won't — each has an incentive to keep what it knows about you. But because both speak MCP, you don't need either of them to. One shared layer they both read and write turns two isolated tools into two front-ends for the same context.
That's multiagentic memory: your context lives in one place you own, and every tool you connect works from it.
Set up your shared context layer →
