Browser Use

Browser Use is a Python library that connects AI agents to real browsers. Instead of scraping static HTML or working through fragile selectors, agents get full control of a live browser session: they can click, type, scroll, fill forms, handle logins, and extract data from any site, including ones that require JavaScript to render.

It's built for developers building AI-powered automation workflows where the target website doesn't offer an API. Think automating research tasks, filling out multi-step web forms, pulling data from behind authentication walls, or running agents that need to navigate real-world web interfaces.

Key capabilities include:

• Multi-tab support so agents can work across several pages in a single session
• DOM extraction that gives the agent a structured view of what's on the page, not just a screenshot
• Vision support for pages where visual context matters
• Parallel agent execution for running tasks at scale across many browser instances
• Session persistence so agents can maintain state across steps, including cookies and login sessions
• LLM-agnostic design meaning you can wire it to OpenAI, Anthropic, or any other model you're using

Compared to tools like Skyvern or Crawl4AI, Browser Use sits closer to the developer-facing, programmable end of the spectrum. You define the agent's goal in natural language, and the library handles translating that into browser actions. There's no low-code UI; it's code-first and designed to be embedded in larger agent pipelines.

The project has broad adoption, with usage reported across Fortune 500 teams and a large open source community. It pairs well with agent frameworks and can be combined with Firecrawl when you need both structured crawling and interactive browsing in the same workflow.