Comparison
awesome-ai-agents vs autogen
Verdict
Pick awesome-ai-agents if provides a curated list of AI autonomous agents, both open and closed-source; pick autogen if autoGen is a Python-based framework for developing agentic AI systems, offering tools for integrating with external models and services, and a no-code GUI for easier interaction.
Markdown twin · awesome-ai-agents alternatives · autogen alternatives
GraphCanon updated Sep 20, 2026
16views this month
vs
Trust & integrity
| Signal | awesome-ai-agents | autogen |
|---|---|---|
| Maintenance | Steady (40d since push) As of Aug 19, 2026 · github_public_v1 | Slowing (155d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Aug 19, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- awesome-ai-agents
- A list of AI autonomous agents
- autogen
- A programming framework for agentic AI
Stars
- awesome-ai-agents
- 30k
- autogen
- 61k
Forks
- awesome-ai-agents
- 3.3k
- autogen
- 9.2k
Open issues
- awesome-ai-agents
- 933
- autogen
- 1.1k
Language
- awesome-ai-agents
- -
- autogen
- Python
Adopt for
- awesome-ai-agents
- Provides a curated list of AI autonomous agents, both open and closed-source.
- autogen
- AutoGen is a Python-based framework for developing agentic AI systems, offering tools for integrating with external models and services, and a no-code GUI for easier interaction.
Persona
- awesome-ai-agents
- -
- autogen
- -
Runtime
- awesome-ai-agents
- -
- autogen
- -
License
- awesome-ai-agents
- Other
- autogen
- CC-BY-4.0
Last pushed
- awesome-ai-agents
- Jul 9, 2026
- autogen
- Apr 15, 2026
Categories
- awesome-ai-agents
- AI Agents
- autogen
- AI Agents, LLM Frameworks
Trust and health
Maintenance
- awesome-ai-agents
- Steady (60%)
- autogen
- Slowing (36%)
Days since push
- awesome-ai-agents
- 40d
- autogen
- 155d
Open issues (now)
- awesome-ai-agents
- 933
- autogen
- 1.1k
Stars delta
- awesome-ai-agents
- +638 (30d)
- autogen
- +897 (30d)
Open issues delta
- awesome-ai-agents
- +73 (30d)
- autogen
- +105 (30d)
Full report
- awesome-ai-agents
- Trust report
- autogen
- Trust report
Typed relationship
awesome-ai-agents alternative autogenawesome-ai-agents serves as an aggregated list of various AI agents, including autonomous data labeling tools like Adala, whereas autogen is a specific framework designed for developing autonomous multi-agent AI applications. The 'alternative' relationship indicates that while awesome-ai-agents directs users to a variety of AI agent options, autogen provides a particular toolset for those focused专
Choose awesome-ai-agents if…
- License: awesome-ai-agents is Other, autogen is CC-BY-4.0.
- Requirements: While 'awesome-ai-agents' does not mention explicit system requirements due to its nature as a list, users should review the individual projects’ documentation.; Users might need specific environments or versions of software depending on which AI agent project they are interested in using from this list..
- awesome-ai-agents serves as an aggregated list of various AI agents, including autonomous data labeling tools like Adala, whereas autogen is a specific framework designed for developing autonomous multi-agent AI applications. The 'alternative' relationship indicates that while awesome-ai-agents directs users to a variety of AI agent options, autogen provides a particular toolset for those focused专
- Tags unique to awesome-ai-agents: agent, artificial-intelligence, autogpt, autonomous-agents.
- When you need to curate or explore a variety of AI agent projects. 'awesome-ai-agents' offers both open source and closed-source AI agent initiatives for easy navigation.
When NOT to use awesome-ai-agents
- When you require real-time collaboration or updates on AI agents; 'awesome-ai-agents' might not have the most updated information in real time.
- If you specifically need a comprehensive, detailed guide for each tool. The repository provides lists but may lack in-depth explanations suitable for those unfamiliar with AI agent systems.
Choose autogen if…
- License: autogen is CC-BY-4.0, awesome-ai-agents is Other.
- Requirements: AutoGen requires Python 3.10 or later.; Installation of AutoGen Studio is optional for no-code GUI interaction.; Ensure trusted MCP servers are used to avoid security risks..
- awesome-ai-agents serves as an aggregated list of various AI agents, including autonomous data labeling tools like Adala, whereas autogen is a specific framework designed for developing autonomous multi-agent AI applications. The 'alternative' relationship indicates that while awesome-ai-agents directs users to a variety of AI agent options, autogen provides a particular toolset for those focused专
- Tags unique to autogen: agentic, agentic-agi, agents, autogen.
- Also covers LLM Frameworks.
- When you need a structured approach to create and manage AI agents with Python.
When NOT to use autogen
- If your project requires a version of Python earlier than 3.10, as AutoGen is not compatible.
- When you need a framework that does not rely on potentially untrusted MCP servers for execution.
- If your project does not require or benefit from the no-code GUI provided by AutoGen Studio.
- When you prefer a framework that does not involve the complexity of setting up and managing multiple MCP servers.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (e2b-dev/awesome-ai-agents) · observed Sep 20, 2026
- GitHub forks (e2b-dev/awesome-ai-agents) · observed Sep 20, 2026
- Last push (e2b-dev/awesome-ai-agents) · observed Jul 9, 2026
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (microsoft/autogen) · observed Sep 20, 2026
- GitHub forks (microsoft/autogen) · observed Sep 20, 2026
- Last push (microsoft/autogen) · observed Apr 15, 2026
- License file (CC-BY-4.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: awesome-ai-agents 30k · autogen 61k (synced Sep 20, 2026).
Common questions
- What is the difference between awesome-ai-agents and autogen?
- awesome-ai-agents: A list of AI autonomous agents. autogen: A programming framework for agentic AI. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-ai-agents over autogen?
- Choose awesome-ai-agents over autogen when License: awesome-ai-agents is Other, autogen is CC-BY-4.0; Requirements: While 'awesome-ai-agents' does not mention explicit system requirements due to its nature as a list, users should review the individual projects’ documentation.; Users might need specific environments or versions of software depending on which AI agent project they are interested in using from this list.; awesome-ai-agents serves as an aggregated list of various AI agents, including autonomous data labeling tools like Adala, whereas autogen is a specific framework designed for developing autonomous multi-agent AI applications. The 'alternative' relationship indicates that while awesome-ai-agents directs users to a variety of AI agent options, autogen provides a particular toolset for those focused专; Tags unique to awesome-ai-agents: agent, artificial-intelligence, autogpt, autonomous-agents; When you need to curate or explore a variety of AI agent projects. 'awesome-ai-agents' offers both open source and closed-source AI agent initiatives for easy navigation.
- When should I choose autogen over awesome-ai-agents?
- Choose autogen over awesome-ai-agents when License: autogen is CC-BY-4.0, awesome-ai-agents is Other; Requirements: AutoGen requires Python 3.10 or later.; Installation of AutoGen Studio is optional for no-code GUI interaction.; Ensure trusted MCP servers are used to avoid security risks.; awesome-ai-agents serves as an aggregated list of various AI agents, including autonomous data labeling tools like Adala, whereas autogen is a specific framework designed for developing autonomous multi-agent AI applications. The 'alternative' relationship indicates that while awesome-ai-agents directs users to a variety of AI agent options, autogen provides a particular toolset for those focused专; Tags unique to autogen: agentic, agentic-agi, agents, autogen; Also covers LLM Frameworks; When you need a structured approach to create and manage AI agents with Python.
- When should I avoid awesome-ai-agents?
- When you require real-time collaboration or updates on AI agents; 'awesome-ai-agents' might not have the most updated information in real time. If you specifically need a comprehensive, detailed guide for each tool. The repository provides lists but may lack in-depth explanations suitable for those unfamiliar with AI agent systems.
- When should I avoid autogen?
- If your project requires a version of Python earlier than 3.10, as AutoGen is not compatible. When you need a framework that does not rely on potentially untrusted MCP servers for execution. If your project does not require or benefit from the no-code GUI provided by AutoGen Studio. When you prefer a framework that does not involve the complexity of setting up and managing multiple MCP servers.
- Is awesome-ai-agents or autogen more popular on GitHub?
- autogen has more GitHub stars (61,036 vs 29,538). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-ai-agents and autogen open source?
- Yes - both are open-source projects on GitHub (awesome-ai-agents: Other, autogen: CC-BY-4.0).
- Where can I find alternatives to awesome-ai-agents or autogen?
- GraphCanon lists graph-backed alternatives at awesome-ai-agents alternatives and autogen alternatives (awesome-ai-agents markdown twin, autogen markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, awesome-ai-agents or autogen?
- awesome-ai-agents: Steady. autogen: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for awesome-ai-agents and autogen?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-ai-agents trust report; autogen trust report.