Learn how ego lite and Skyvern 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
8 hours agoRepository age
3 yearsVersion
v1.0.56License
AGPL-3.0Self-hosted
YesRepository
skyvern-ai/skyvern
Both ego lite and Skyvern 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.
Both tools have similar popularity levels, with ego lite having 20,122 stars and Skyvern having 23,286 stars on GitHub. In terms of developer contributions, Skyvern has 2,222 forks, indicating strong developer engagement.
ego lite is growing faster, adding 3,568 stars in the last 30 days (+22%) against adding 201 stars for Skyvern (+0.9%). ego lite is the smaller project of the two, so it is closing the gap rather than extending a lead.
Both projects show recent activity, with ego lite last updated 13 hours ago and Skyvern 8 hours ago.
Both tools share common technology foundations, being built with JavaScript, Bash, Typescript. However, they differ in their additional technology choices: Skyvern leverages CSS, JSX, Python.
Skyvern has been in development longer, starting 3 years ago, compared to ego lite which began 6 months ago. This 2.2-year head start suggests Skyvern may have more mature features and established processes.
ego lite uses the MIT license, which is more permissive than Skyvern's AGPL-3.0 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.
Skyvern provides self-hosting options for complete data control and customization, while ego lite may be primarily cloud-based or require different deployment approaches.