Learn how Skyvern and Steel differ in their key features, development activity, technology stack and community adoption, so you can decide which of these browser automation for ai tools is best for you.
Last 30 days
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Last 30 days
Last commit
Repository age
Version
License
Repository

Both Skyvern and Steel have their unique strengths and serve similar purposes effectively. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
Skyvern significantly outpaces Steel in community adoption with 22,790 stars compared to 7,509 stars on GitHub. This 3.0x difference suggests Skyvern has a much larger and more active community. In terms of developer contributions, Skyvern has 2,140 forks, indicating strong developer engagement.
Steel is growing faster, adding 155 stars in the last 30 days (+2.1%) against adding 267 stars for Skyvern (+1.2%). Steel is the smaller project of the two, so it is closing the gap rather than extending a lead.
Both projects show recent activity, with Skyvern last updated 20 hours ago and Steel 12 hours ago.
Both tools share common technology foundations, being built with JavaScript, CSS, Bash, Typescript, JSX. However, they differ in their additional technology choices: Skyvern uses Python.
Both projects started around the same time, with Skyvern beginning 2 years ago and Steel 2 years ago.
The projects use different licenses: Skyvern is licensed under AGPL-3.0 while Steel uses Apache-2.0. Consider the licensing requirements when choosing for your project.
Both tools serve similar use cases in Browser Automation for AI. However, they also have distinct specializations: Skyvern also focuses on Workflow Automation while Steel extends into Browser Automation.