CoCursor

Team AI Collaboration Tool for Cursor IDE

中文文档 • Releases • Installation • Features

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The efficiency gap between those who can use AI and those who can’t is 100x. This is not an exaggeration.

What is CoCursor?

CoCursor is a VS Code/Cursor extension that empowers teams to collaborate with AI more effectively. It combines work analytics, semantic search of AI conversations, skill sharing marketplace, and automated reporting - all running locally with complete data privacy.

Built with:

• Backend: Go 1.24 + Gin + DDD Architecture
• Frontend: VS Code Extension + React + TypeScript
• Team Collaboration: P2P Architecture + mDNS Discovery + WebSocket Real-time Sync
• RAG: Qdrant Vector Database + Embedding Models (supports local deployment)
• Workflow: OpenSpec-driven Development

Features

📊 Work Analysis Dashboard

Track every AI collaboration session automatically.

• Monitor your work sessions in Cursor
• Analyze work types, tech stacks, and code changes
• One-click daily/weekly report generation

No more spending 30 minutes writing work reports. AI helps you work and helps you report.

🔍 AI Conversation Semantic Search (RAG)

Every question, code snippet, and solution you’ve discussed with AI is in your Cursor chat history.

CoCursor’s RAG features:

• Automatically index all your conversations in Cursor
• Semantic search: find historical conversations using natural language
• "How did I solve that database connection issue last week?" → Found instantly

Your AI conversations are no longer one-time use - they become searchable, reusable knowledge.

🤝 Team Skill Marketplace

One person knowing AI isn’t enough - the whole team needs to know.

• Publish your AI Skills to the team with one click
• Team members can install instantly and gain the same capabilities
• P2P LAN direct transfer, no server involved, data stays secure

Let the weakest member on the team use the strongest member’s AI skills.

⚡ Workflow Engine

Drive AI workflows with OpenSpec specifications:

• Requirements → Design → Implementation, standardized end-to-end
• Not "what do you think we should do" but "everyone follows this process"
• AI executes according to specs, results are predictable

Installation

From VS Code Marketplace

Search for "CoCursor" in the VS Code/Cursor Extensions marketplace and install.

From GitHub Releases

Download the VSIX file for your platform from Releases:

• cocursor-linux-x64.vsix - Linux x64
• cocursor-win32-x64.vsix - Windows x64
• cocursor-darwin-x64.vsix - macOS Intel
• cocursor-darwin-arm64.vsix - macOS Apple Silicon

Install in VS Code/Cursor:

code --install-extension cocursor-<platform>.vsix

Build from Source

# Clone the repository
git clone https://github.com/toheart/cocursor.git
cd cocursor

# Build backend (requires Go 1.24+)
cd backend
make build-all

# Build frontend extension (requires Node.js 18+)
cd ../co-extension
npm install
make build

# Package as VSIX
npx @vscode/vsce package

Quick Start

1. Open CoCursor Panel: Click the CoCursor icon in the VS Code/Cursor sidebar
2. Work Analysis: View your AI collaboration statistics and generate reports
3. RAG Search: Search through your historical AI conversations
4. Team Collaboration: Create or join a team to share skills

Architecture

cocursor/
├── backend/                 # Go Backend Daemon (DDD Architecture)
│   ├── cmd/                 # Application entry points
│   ├── internal/
│   │   ├── domain/          # Domain models and business logic
│   │   ├── application/     # Application services
│   │   ├── infrastructure/  # External integrations
│   │   └── interfaces/      # HTTP handlers
│   └── pkg/                 # Shared packages
├── co-extension/            # VS Code Extension (React + TypeScript)
│   ├── src/
│   │   ├── extension.ts     # Extension entry point
│   │   ├── webview/         # React UI components
│   │   └── daemon/          # Daemon process manager
│   └── resources/           # Static assets
└── openspec/                # OpenSpec specifications

Privacy & Security

• 100% Local Execution: All data processing happens on your machine
• No Cloud Services: Your code and conversations never leave your computer
• P2P Team Collaboration: Direct peer-to-peer communication within your LAN
• Open Source: Fully auditable codebase

Roadmap

Phase	Capability	Value
Now	Personal conversation search	Personal knowledge retention
Next	MCP Integration	Connect more data sources
Future	Team Brain	Aggregate all team members’ AI conversations into a team knowledge base

Imagine: A new team member doesn’t need to ask veterans - just search the Team Brain: "What pitfalls did we encounter with this module?" - Everyone’s experience is right there.

Contributing

Contributions are welcome! Please read our contributing guidelines before submitting PRs.

License

CoCursor Non-Commercial License - Free for non-commercial use only.

Links

• GitHub: https://github.com/toheart/cocursor
• VS Code Marketplace: https://marketplace.visualstudio.com/items?itemName=tanglyan-cocursor.cocursor

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If you’re also leading a team and thinking about how to help your team use AI better - let’s connect!