Back to products
Context Sync

Context Sync

Persistent AI memory across Claude Desktop & Cursor IDE

Website github.com
Overview

What it is

Developers use a pile of AI assistants — but each one lacks full project context. Vernon fixes that by becoming the universal context layer: a single source of truth shared across Claude, Copilot, Zed, Cursor, and more. Install once, and every AI tool understands your project instantly.

Intent

I need it when

Integrate optional Notion documentation lookup into AI coding workflows without manual context switching

Context Sync offers read-only Notion integration via notion() tool with search and read actions. Users can query project documentation stored in Notion directly within their AI coding session, keeping context in one place.

Enable AI coding assistants to understand project structure and make informed code suggestions without manual file navigation

Context Sync provides structure() and search() tools that let AI agents explore the codebase systematically, and read_file() for focused inspection. This reduces the need for users to manually paste file contents or explain directory layouts.

Capture and preserve important development decisions and constraints so they persist beyond a single conversation

The remember() tool lets users log decisions, constraints, and caveats with type classification. These are stored persistently and recalled in future sessions, ensuring the AI maintains awareness of project-specific rules and prior choices.

Automatically track code changes and context hotspots using Git hooks to inform AI about recent activity

Context Sync installs optional Git hooks (post-commit, pre-push, post-merge, post-checkout) that automatically capture context. The git tool then provides status, hotspots, coupling, and blame analysis, giving AI agents awareness of recent changes and code relationships.

Maintain persistent project context across multiple AI coding sessions to avoid re-explaining codebase details

Context Sync stores project identity, tech stack, active decisions, and constraints in a local SQLite database, making this information retrievable via MCP tools across sessions. Users call recall() at session start to recover prior context instead of re-briefing the AI model.

Drop

Not a fit when

  • User requires commercial support or SLA guarantees for production systems
  • Organization prohibits open-source tools or requires vendor indemnification
  • Project does not use any of the supported AI coding tools (Claude Desktop, Cursor, VS Code Copilot, Continue.dev, Zed, Windsurf, Codeium, TabNine, Codex CLI, Claude Code, Antigravity)
  • User needs real-time multi-user collaboration on shared project context across distributed teams
  • Codebase is not version-controlled with Git or lacks Git repository structure
Commercials

Pricing

Free, open-source