Browser-Use Automation - Setup Guide¶
Source: browser-use/browser-use - 97,000+ ★ | Python Category: Automation / Browser-Use Quality Tier: 🟢 Production (97K+ GitHub stars, active development)
Browser-use replaces Playwright/Selenium for sites defended by anti-bot systems. Instead of writing brittle selectors, you describe the task in natural language and a vision-capable LLM drives the browser like a human. It handles CAPTCHAs, JS-heavy rendering, and anti-bot detection natively.
How It Works¶
- You describe a goal ("log in to this site, navigate to the pricing page, extract the plans")
- A vision-capable model (Claude Sonnet, GPT-4 class) screenshots the page
- The model decides the next action: click, type, scroll, navigate
- Actions execute through a real browser until the task completes
This closed loop is why browser-use succeeds where selector-based automation fails: it adapts to dynamic DOMs, obfuscated class names, and layout shifts.
Installation¶
python3 -m venv venv-browser
source venv-browser/bin/activate
pip install browser-use
python3 -m playwright install chromium # browser-use drives Playwright under the hood
Quick Start¶
import asyncio, os
from browser_use import Agent, ChatAnthropic
async def main():
llm = ChatAnthropic(
model="claude-sonnet-4-20250514",
api_key=os.getenv("ANTHROPIC_API_KEY"),
)
agent = Agent(
task="Go to linkedin.com/login, log in, navigate to jobs",
llm=llm,
)
result = await agent.run()
print(result)
asyncio.run(main())
Requirements: - Python 3.11+ - A vision-capable LLM API key (browser-use is LLM-agnostic: Anthropic, OpenAI, Gemini, or local Ollama models) - ~5 GB free disk for browser binaries
When to Use Browser-Use¶
| Use browser-use for | Stick with plain Playwright for |
|---|---|
| Sites with Cloudflare / anti-bot walls | Simple form filling on undefended sites |
| Dynamic SPAs with obfuscated selectors | API-authenticated platforms |
| CAPTCHA-protected flows | Bulk scraping (LLM calls add cost) |
| Multi-step logins with security checkpoints | Speed-critical extraction |
Cost note: Every action costs an LLM call. For high-volume scraping, plain Playwright or direct APIs are far cheaper. Browser-use shines on flows where automation gets blocked, not where it merely works.
Headless Limitations¶
Anti-bot systems fingerprint headless browsers. Browser-use works best when the runtime environment looks like a real user:
- Residential or mobile IPs pass Cloudflare checks where datacenter IPs get challenged
- Headful mode with persistent profiles survives platform login flows (cookies + crypto-bound session keys persist together)
- On headless servers, pair with Xvfb for a virtual display
Xvfb :99 -screen 0 1920x1080x24 -ac &
export DISPLAY=:99
Verification¶
python3 -c "import browser_use; print('browser-use ready')"
A successful smoke test: run the Quick Start against a public site and confirm the agent extracts the expected data.
Notes¶
- Production-grade: 97K+ GitHub stars, used across the AI automation ecosystem
- Vision-first: No CSS selectors needed - the model sees the page like a human
- Best for: Anti-bot-defended platforms, dynamic SPAs, CAPTCHA flows
- Complementary: Use alongside plain Playwright - browser-use for vision tasks, Playwright for cheap API-level control
- Related: See Playwright Social Media Automation and Midscene
Setup guide by CorpusIQ. Source: browser-use/browser-use.
Integration with CorpusIQ¶
CorpusIQ is the connector layer that lets AI assistants read the systems a business already runs on - accounting, payments, CRM, email, files and analytics - and answer with the source named. It is read-only by design: it retrieves data and never writes to, or acts in, a connected system, which is what makes it safe to point at live accounts.
This page is part of the CorpusIQ directory, the reference we maintain for the MCP server and agent-skill ecosystem. Run alongside CorpusIQ, a third-party server like this one can be combined with a company's own business data in a single answer.