Home/Compare/awesome-prompts vs autogen

Comparison

awesome-prompts vs autogen

Verdict

Pick awesome-prompts when license: awesome-prompts is GPL-3.0, autogen is CC-BY-4.0; pick autogen when license: autogen is CC-BY-4.0, awesome-prompts is GPL-3.0.

Markdown twin · awesome-prompts alternatives · autogen alternatives

GraphCanon updated today

awesome-prompts logo

awesome-prompts

ai-boost/awesome-prompts

8.4kpushed Jul 11, 2026
vs
autogen logo

autogen

microsoft/autogen

60kpushed Apr 15, 2026

Trust & integrity

Signalawesome-promptsautogen
Maintenance
Very active (0d since push)
As of today · github_public_v1
Steady (87d since push)
As of today · github_public_v1
Provenance
Not a fork · Personal account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No lockfile
As of 1d · none

Tagline

awesome-prompts
Curated list of chatgpt prompts from the top-rated GPTs in the GPTs Store. Prompt Engineering, prompt attack & prompt protect. Advanced Prompt Engineering papers.
autogen
A programming framework for agentic AI

Stars

awesome-prompts
8.4k
autogen
60k

Forks

awesome-prompts
798
autogen
9.0k

Open issues

awesome-prompts
35
autogen
945

Language

awesome-prompts
-
autogen
Python

Adopt for

awesome-prompts
-
autogen
AutoGen is a Python-based framework for developing and managing agentic AI systems. It includes the AutoGen Studio for no-code GUI setup, integrating with various models.

Persona

awesome-prompts
-
autogen
-

Runtime

awesome-prompts
-
autogen
-

License

awesome-prompts
GPL-3.0
autogen
CC-BY-4.0

Last pushed

awesome-prompts
Jul 11, 2026
autogen
Apr 15, 2026

Categories

awesome-prompts
LLM Frameworks
autogen
AI Agents, LLM Frameworks

Trust and health

Maintenance

awesome-prompts
Very active (96%)
autogen
Steady (60%)

Days since push

awesome-prompts
0d
autogen
87d

Open issues (now)

awesome-prompts
35
autogen
945

Owner type

awesome-prompts
User
autogen
Organization

Full report

awesome-prompts
Trust report

Choose awesome-prompts if…

  • License: awesome-prompts is GPL-3.0, autogen is CC-BY-4.0.
  • Tags unique to awesome-prompts: awesome, awesome-list, gpt4, gpts.
  • More recently updated (last pushed Jul 11, 2026).

When NOT to use awesome-prompts

  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.

Choose autogen if…

  • License: autogen is CC-BY-4.0, awesome-prompts is GPL-3.0.
  • Requirements: Min 4 GB RAM; AutoGen requires Python 3.10 or later.; Ensure security when connecting to MCP servers due to the potential for local command execution and sensitive information exposure..
  • Tags unique to autogen: agentic-agi, agents, ai, autogen.
  • Also covers AI Agents.
  • You need a framework that supports integration with multiple AI models via OpenAI's chat completion client.

When NOT to use autogen

  • If you require tools supporting multiple programming languages beyond Python, as AutoGen is strictly a Python-based framework.
  • When deploying in environments where connecting to external servers (like those used by MCP) could pose security risks or is prohibited.
  • You need solutions which do not involve additional installations for server components such as `playwright/mcp`, as AutoGen requires this setup for certain functionalities.

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: awesome-prompts 8.4k · autogen 60k (synced Jul 11, 2026).

Common questions

What is the difference between awesome-prompts and autogen?
awesome-prompts: Curated list of chatgpt prompts from the top-rated GPTs in the GPTs Store. Prompt Engineering, prompt attack & prompt protect. Advanced Prompt Engineering papers.. autogen: A programming framework for agentic AI. See the comparison table for live GitHub stats and shared categories.
When should I choose awesome-prompts over autogen?
Choose awesome-prompts over autogen when License: awesome-prompts is GPL-3.0, autogen is CC-BY-4.0; Tags unique to awesome-prompts: awesome, awesome-list, gpt4, gpts; More recently updated (last pushed Jul 11, 2026).
When should I choose autogen over awesome-prompts?
Choose autogen over awesome-prompts when License: autogen is CC-BY-4.0, awesome-prompts is GPL-3.0; Requirements: Min 4 GB RAM; AutoGen requires Python 3.10 or later.; Ensure security when connecting to MCP servers due to the potential for local command execution and sensitive information exposure.; Tags unique to autogen: agentic-agi, agents, ai, autogen; Also covers AI Agents; You need a framework that supports integration with multiple AI models via OpenAI's chat completion client.
When should I avoid awesome-prompts?
LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
When should I avoid autogen?
If you require tools supporting multiple programming languages beyond Python, as AutoGen is strictly a Python-based framework. When deploying in environments where connecting to external servers (like those used by MCP) could pose security risks or is prohibited. You need solutions which do not involve additional installations for server components such as playwright/mcp, as AutoGen requires this setup for certain functionalities.
Is awesome-prompts or autogen more popular on GitHub?
autogen has more GitHub stars (59,658 vs 8,440). Stars measure visibility, not whether either tool fits your constraints.
Are awesome-prompts and autogen open source?
Yes - both are open-source projects on GitHub (awesome-prompts: GPL-3.0, autogen: CC-BY-4.0).
Where can I find alternatives to awesome-prompts or autogen?
GraphCanon lists graph-backed alternatives at awesome-prompts alternatives and autogen alternatives (awesome-prompts 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-prompts or autogen?
awesome-prompts: Very active. autogen: Steady. 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-prompts and autogen?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-prompts trust report; autogen trust report.