AgentOS vs Langflow

Langflow significantly outpaces AgentOS in community adoption with 156,070 stars compared to 683 stars on GitHub. This 228.5x difference suggests Langflow has a much larger and more active community. In terms of developer contributions, Langflow has 10,252 forks, indicating strong developer engagement.

AgentOS is growing faster, adding 10 stars in the last 30 days (+1.5%) against adding 765 stars for Langflow (+0.5%). AgentOS is the smaller project of the two, so it is closing the gap rather than extending a lead.

Both projects show recent activity, with AgentOS last updated 7 hours ago and Langflow 5 hours ago.

Both tools share common technology foundations, being built with JavaScript, Typescript. However, they differ in their additional technology choices: Langflow leverages CSS, Bash, JSX, Python.

Langflow has been in development longer, starting 4 years ago, compared to AgentOS which began 1 year ago. This 2.8-year head start suggests Langflow may have more mature features and established processes.

Langflow uses the MIT license, which is more permissive than AgentOS's Apache-2.0 license, potentially offering greater flexibility for commercial use and integration.

Both tools serve similar use cases in AI Agent Platforms. However, they also have distinct specializations: Langflow extends into Low-Code/No-Code, LLM Application Frameworks.

Langflow provides self-hosting options for complete data control and customization, while AgentOS may be primarily cloud-based or require different deployment approaches.