Give Copilot context from your entire AI stack

GitHub Copilot is the most widely adopted AI coding assistant, with inline suggestions that complete code as you type and Copilot Chat for conversational coding in VS Code. But Copilot operates with a narrow context window — it sees the current file, open tabs, and recent chat history. It has no memory of what happened in previous sessions, and it has no visibility into decisions made in other AI tools.

With MCP support now available in VS Code, Swylink gives Copilot a persistent memory layer that extends far beyond its built-in context. When you spent an hour in Claude Code debugging a race condition and documenting the fix, Copilot can now access that context. When Cursor's Composer restructured your API layer last week, Copilot's inline suggestions reflect those architectural decisions.

This transforms Copilot from a stateless autocomplete engine into a context-aware coding partner. Its inline suggestions become more accurate because they are informed by the full history of decisions across your AI stack. Copilot Chat conversations become more productive because the AI already knows what has been tried, what worked, and what was deliberately avoided. The workspace context that Copilot already uses is now enriched with cross-tool, cross-session intelligence.

Copilot interactions generate specific types of context that Swylink captures: code completion patterns that reveal preferred coding conventions, Copilot Chat decisions about implementation approaches, workspace-level architectural discussions, test generation strategies and coverage decisions, code review feedback from Copilot-assisted reviews, and refactoring patterns chosen during Chat-guided restructuring. This context flows to every other tool in your stack — when Claude Code starts a new session, it can search for what Copilot Chat discussed and continue from there.