Learn how Agno and IronClaw differ in their key features, development activity, technology stack and community adoption, so you can decide which of these ai agent platforms is best for you.
Last 30 days
Last commit
2 days agoRepository age
5 yearsVersion
v3.1.12License
Apache-2.0Repository
agno-agi/agno
Last 30 days
Last commit
4 days agoRepository age
9 monthsVersion
v1.4.1License
Apache-2.0Self-hosted
YesRepository
nearai/ironclaw
Agno appears to have several advantages over IronClaw, particularly in popularity, growth and maturity. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
Agno significantly outpaces IronClaw in community adoption with 43,101 stars compared to 12,715 stars on GitHub. This 3.4x difference suggests Agno has a much larger and more active community. In terms of developer contributions, Agno has 6,261 forks, indicating strong developer engagement.
Agno is growing faster, adding 467 stars in the last 30 days (+1.1%) against adding 70 stars for IronClaw (+0.6%). Agno is both larger and pulling further ahead.
Both projects show recent activity, with Agno last updated 2 days ago and IronClaw 4 days ago.
Both tools share common technology foundations, being built with Bash, Python. However, they differ in their additional technology choices: IronClaw leverages JavaScript, CSS, Typescript, JSX, Rust, C.
Agno has been in development longer, starting 5 years ago, compared to IronClaw which began 9 months ago. This 3.8-year head start suggests Agno may have more mature features and established processes.
Both projects use the Apache-2.0 license, providing identical terms for usage and distribution.
Both tools serve similar use cases in AI Agent Platforms. However, they also have distinct specializations: Agno also focuses on LLM Application Frameworks while IronClaw extends into AI Personal Assistants.
IronClaw provides self-hosting options for complete data control and customization, while Agno may be primarily cloud-based or require different deployment approaches.