Give Cursor a memory that never forgets

Cursor is one of the most powerful AI-first editors available, but its context model has a fundamental limitation: it is project-scoped and session-limited. Your .cursorrules file defines project conventions, and Cursor's Composer can orchestrate multi-file edits with impressive accuracy. But the moment you close that session or switch to Claude Code for a complex refactoring task, all of that accumulated context — the architectural decisions you discussed, the API patterns you settled on, the dependency trade-offs you evaluated — vanishes.

Swylink bridges this gap by acting as a persistent semantic memory layer. Every decision made during a Cursor Composer session is automatically captured with structured metadata: what changed, why it changed, which files were affected, and what tags describe the domain. When you later open Claude Code to tackle a deeper refactoring or debug a production issue, you can search "why did we restructure the auth module" and instantly retrieve the reasoning from your Cursor session.

This is especially valuable for developers who use Cursor for rapid prototyping and multi-file editing, then switch to Claude Code for complex architectural work. Without Swylink, you would need to re-explain every prior decision. With Swylink, your AI tools share a unified memory — Cursor's speed meets Claude Code's depth, with zero context loss between them.

When you work in Cursor, Swylink captures the decisions that matter: architecture choices made during Composer sessions, package selections and why alternatives were rejected, API design decisions and endpoint structures, file restructuring rationale and module boundaries, naming conventions established during refactoring, and performance trade-offs discussed with the AI. Later, when you open Claude Code or Windsurf, you can search by meaning — ask "why did we choose this API structure" and get the exact decision from your Cursor session, complete with the reasoning and affected files.