open-cowork: Open-source AI agent desktop app for Windows & macOS

by OpenCoworkAI · MCP Server · ★ 2.2k

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install open-cowork

brew install --cask --no-quarantine open-cowork
git clone https://github.com/OpenCoworkAI/open-cowork.git

Taken from the project's README on GitHub. Check the security audit before running it.

Security audit verdict: SAFE · quality 68/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

ai-agentai-codingai-toolsanthropicclaude-codecoding-agentcomputer-usedesktop-appelectronmcp

Quick Facts

Stars2,219
Forks320
LanguageTypeScript
CategoryMCP Server
LicenseMIT
Quality Score68/100
Open Issues94
Last Updated2026-10-20
Created2026-01-13
Platformsclaude-code, cli, mcp, node
Est. Tokens~18k

About open-cowork

🚀 Open Cowork: Your Personal AI Agent Desktop App • Open Source Claude Cowork • One-Click Install 中文文档 • Features • Demo • Downloads • Quick Start • Skills Library Open Cowork is a free, open-source AI agent desktop application for Windows and macOS. It wraps Claude Code, OpenAI, Gemini, DeepSeek, and other AI models into a user-friendly GUI with one-click installation — no coding required.

Compatible Skills

These tools work well together with open-cowork for enhanced workflows:

  • goodable — semantic(0.20)+complementary+rare_topics+same_lang+similar_pop+shared_platform (57%)
  • eigent — semantic(0.74)+rare_topics+same_lang+shared_platform (49%)

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

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