awesome_ai_agents and awesome-ai-agents-2026

These are **competitors** — both are curated directory projects attempting to comprehensively catalog AI agents and related tools in the same space, with users likely choosing one as their primary reference based on size (1,500+ vs 300+ resources) and update frequency.

awesome_ai_agents
57
Established
Maintenance 6/25
Adoption 10/25
Maturity 16/25
Community 25/25
Maintenance 13/25
Adoption 8/25
Maturity 9/25
Community 18/25
Stars: 1,468
Forks: 357
Downloads:
Commits (30d): 0
Language:
License: Apache-2.0
Stars: 54
Forks: 15
Downloads:
Commits (30d): 0
Language:
License:
No Package No Dependents
No Package No Dependents

About awesome_ai_agents

jim-schwoebel/awesome_ai_agents

🤖 A comprehensive list of 1,500+ resources and tools related to AI agents.

The repository organizes 1,500+ resources across building blocks—frameworks (AutoGen, LangChain, CrewAI), LLM models, datasets, and benchmarks—enabling developers to understand the full stack for agent development. It structures discovery by use case (coding agents, customer service, video generation) and development phase (learning, building, deploying), with dedicated sections for security, testing, and ethics considerations. The collection emphasizes hands-on exploration through live agent demos, courses, and community contributions, positioning itself as a development-focused knowledge base rather than purely informational.

About awesome-ai-agents-2026

caramaschiHG/awesome-ai-agents-2026

🤖 The most comprehensive list of AI agents, frameworks & tools in 2026. 300+ resources · 20+ categories · Updated monthly.

Organizes 300+ AI agent tools across specialized domains—coding, frameworks, browser automation, voice, creative, workflow, CRM, research, and self-hosted solutions—with structured categorization by capability rather than just listing resources. Covers emerging categories like multi-agent platforms, safety guardrails, cybersecurity agents, and industry-specific protocols/standards, plus market statistics and learning resources. Community-driven with monthly updates and PR-based contributions, enabling developers to discover tools matched to specific use cases rather than navigating fragmented documentation.

Scores updated daily from GitHub, PyPI, and npm data. How scores work