Skyvern
Skyvern automates browser-based workflows using language models and computer vision. Instead of fixed selectors, it recognises page elements visually and can therefore work on websites for which no dedicated script has been written.
- Project
- Skyvern
- Publisher
- Skyvern
- Repository
- github.com/Skyvern-AI/skyvern
- Documentation
- www.skyvern.com/docs
- Languages
- Python, TypeScript
- Category
- Browser agents
What is Skyvern?
Traditional browser automation relies on DOM parsing and XPath selectors that break when layouts change. Skyvern instead uses vision-capable language models and several agents that interpret a page, plan actions and carry them out. It includes a Playwright-compatible SDK for Python and TypeScript and a no-code workflow builder.
The core logic is released under the AGPL-3.0 licence and can be run locally via pip or Docker Compose. A managed cloud version is also available; according to the README, anti-bot measures are only included there.
Core capabilities
- AI-powered page commands
- Performing actions in natural language, extracting structured data against a JSON schema and validating page state – combinable with classic Playwright selectors, with AI as a fallback.
- Workflows
- Chained blocks such as browser task, data extraction, validation, loops, file parsing, HTTP requests and custom code.
- Forms and downloads
- Filling out forms based on a navigation goal and downloading files.
- Authentication
- Login with stored credentials, support for various 2FA methods and integration with Bitwarden or a custom credential service.
- Observation and integration
- Livestreaming the browser viewport to follow and intervene; integration via MCP and with Zapier, Make.com and n8n.
When Skyvern fits
Skyvern fits recurring tasks in web portals without a suitable API – retrieving data from customer portals, downloading invoices or filling out forms across many similar sites, for example. Where a stable API exists, it is usually the more reliable choice.
Using Skyvern effectively in an AI-first business model
A browser agent acts with the rights of the account it is logged in with. Clarify in advance which portals it may use, with which account, and which actions – orders, submissions or changes, for example – require human approval. Also check the terms of use of each website.
The livestream and structured outputs help trace runs. In operation, you additionally need test cases that show whether a workflow still delivers the right result after a website changes.
From tool to outcome
In AI-first coaching you clarify which outcomes AI agents should be accountable for in your go-to-market and within which framework. REVAGO then designs, builds and runs your system. You pay for results – not for activity.
Frequently asked questions
What is Skyvern?
Skyvern is a browser automation tool that uses language models and computer vision. It offers a Playwright-compatible SDK for Python and TypeScript and a no-code workflow builder, and it can be run locally or as a managed cloud version.
How does Skyvern differ from Playwright or Selenium?
Playwright and Selenium control the browser through selectors defined in code. Skyvern builds on Playwright and adds natural-language commands that recognise elements visually. Both approaches can be combined, for example selectors first with AI as a fallback.
What licence is Skyvern released under?
The core logic in the open-source repository is released under the AGPL-3.0 licence. According to the project, anti-bot measures are only included in the managed cloud version.
Further reading in the wiki
A neutral overview, not a recommendation of individual providers. REVAGO is not affiliated with the listed projects. Descriptions are based on the projects’ public information; features and licences may change.