Learn how ego lite 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
Last commit
13 hours agoRepository age
6 monthsVersion
v2.1.0License
MITRepository
citrolabs/ego-lite
Last 30 days
Last commit
10 hours agoRepository age
2 yearsVersion
v0.5.4-betaLicense
Apache-2.0Self-hosted
YesRepository
steel-browser
Both ego lite 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.
ego lite leads in popularity with 20,122 stars vs 7,875 stars for Steel. The 156% higher star count indicates stronger community adoption. In terms of developer contributions, ego lite has 1,123 forks, indicating strong developer engagement.
ego lite is growing faster, adding 3,568 stars in the last 30 days (+22%) against adding 171 stars for Steel (+2.2%). ego lite is both larger and pulling further ahead.
Both projects show recent activity, with ego lite last updated 13 hours ago and Steel 10 hours ago.
Both tools share common technology foundations, being built with JavaScript, Bash, Typescript. However, they differ in their additional technology choices: Steel leverages CSS, JSX.
Steel has been in development longer, starting 2 years ago, compared to ego lite which began 6 months ago. This 1.5-year head start suggests Steel may have more mature features and established processes.
ego lite uses the MIT license, which is more permissive than Steel's Apache-2.0 license, potentially offering greater flexibility for commercial use and integration.
Both tools serve similar use cases in Browser Automation for AI. However, they also have distinct specializations: ego lite also focuses on Web Browsers.
Steel provides self-hosting options for complete data control and customization, while ego lite may be primarily cloud-based or require different deployment approaches.