ag2: AG2 (formerly AutoGen): The Open-Source AgentOS.Join us at

by ag2ai · MCP Server · ★ 5.0k

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How to install ag2

pip install ag2[openai]
pip install 'ag2[openai]'

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

Security audit verdict: SAFE · quality 69/100

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.

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Quick Facts

Stars5,048
Forks782
LanguagePython
CategoryMCP Server
LicenseApache-2.0
Quality Score69/100
Open Issues78
Last Updated2026-11-06
Created2024-11-11
Platformsmcp, python
Est. Tokens~18k

About ag2

📚 Documentation | 💡 Examples | 🤝 Contributing</a

Compatible Skills

These tools work well together with ag2 for enhanced workflows:

  • edict — semantic(0.16)+complementary+shared_fw(autogen)+same_lang+similar_pop+shared_platform (59%)
  • open-terminal — semantic(0.23)+complementary+same_lang+similar_pop+shared_platform (58%)
  • awesome_ai_agents — semantic(0.40)+complementary+rare_topics+similar_pop (58%)
  • FlashLearn — semantic(0.20)+complementary+rare_topics+same_lang+similar_pop+shared_platform (57%)
  • openai-agents-python — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (56%)

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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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