Browser Use, Make websites accessible for AI agents.

#opensource #browseruse #agents #ai

In this article, we review Browser Use. You will learn:

What is Browser Use
Quickstart guide

What is Browser Use

Browser Use is a Python library for AI browser automation with 104k+ GitHub stars. Connect any LLM and run locally or self-hosted.

I came across the Browser Use when I was checking out the Page Agent.

When you sign up on Browser Use, you will see the above screen. To give it a shot, since a new user get 10 free tasks, I wrote the following prompt and submitted:

Find the cheapest flight from London to Vancouver

It ran for some time and gave this result.

You will find two tabs on the right:

Browser
Files

The one I opened is an output produced at the end of the conversation. But this is just one example.

Use cases

I found more examples in their Github README such as:

Open those links, you will find demo videos, demonstrating how powerful browser use is.

Quickstart guide

If you want to use Browser Use in your agent (Claude Code, Codex, Cursor, Hermes, OpenClaw, etc.), paste this prompt, and it sets everything up itself:

Install or upgrade browser-use to the latest stable version with uv using Python 3.12, run `browser-use skill install` to register the skill, and connect it to my browser. If setup or connection fails, follow https://github.com/browser-use/browser-harness/blob/main/install.md.

Then tell your agent what you want done.

Python library: the easiest way to automate the web

Want to automate the web at scale, from your own code, and with any LLM? Use the Python library:

Install Browser Use (Python >= 3.11):

uv add browser-use
# or: pip install browser-use

Add your LLM API key to .env. Get one from Browser Use Cloud, or bring your own provider key:

# .env
BROWSER_USE_API_KEY=your-key
# GOOGLE_API_KEY=your-key
# ANTHROPIC_API_KEY=your-key

Run your first agent:

import asyncio

from browser_use import Agent, ChatBrowserUse

async def main():
    agent = Agent(
        task="Find the number of stars of the browser-use repo",
        llm=ChatBrowserUse(model='openai/gpt-5.5'),
        # llm=ChatBrowserUse(model='bu-2-0'),  # Browser Use's optimized model
        # llm=ChatOpenAI(model='gpt-5.5'),
        # llm=ChatAnthropic(model='claude-opus-4-8'),  # Sonnet also works well
    )
    history = await agent.run()

if __name__ == "__main__":
    asyncio.run(main())

About me:

Hey, my name is Ramu Narasinga. Email: ramu.narasinga@gmail.com

I spent 3+ years studying OSS codebases and wrote 400+ articles on what makes the production-grade. Now I'm putting that into practice differently - instead of writing every fix myself, I run coding agents that do it.

How it works? Register your machine as a Runtime, point it at your repo. Agents pick up issues. write the fix, open the PR. You just review, they execute.