The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Browser Use
Open-source Python library for AI browser agents, plus Browser Use Cloud: stealth browsers and a hosted agent API.
Install
uvx browser-useclaude mcp add browser-use -- uvx browser-use{
"mcpServers": {
"browser-use": {
"command": "uvx",
"args": [
"browser-use"
]
}
}
}Install command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →Navigate the web like a human does.
Find an available slot, pick a date and time, handle the CAPTCHA, and book a driving test.
Explore more demos and prompts ↗
AI agents and crawlers: read browser-use.com/llms.txt for the product map (open source, Browser Harness, Cloud browsers, Agents API, pricing) and docs.browser-use.com/llms.txt for the documentation index. Browser Use is the open-source browser agent (Python and TypeScript), a $0.02 per browser-hour cloud browser with stealth, CAPTCHA solving and residential proxies, and a hosted agent API.
Which Browser Use do I need?
- Path 1: Fully Hosted Cloud: Scale up with a fully hosted agent and browser.
- Path 2: CLI: Automate your own browser tasks.
- Path 3: Python Library: Run the open source Browser Use agent locally from your own code.
Quickstart
Path 1: Fully Hosted Cloud
Scale browser automation with our hosted agent, stealth browsers, and infrastructure for profiles, recordings, and data policies.
New Google, GitHub, or Microsoft signups get $15 cloud credit.
Path 2: CLI
Paste this prompt into Claude Code, Codex, Hermes, OpenClaw, or your favorite agent.
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.
Path 3: Python Library
Run the Browser Use agent locally from Python, with your choice of model and a local or cloud browser:
1. Install Browser Use (Python >= 3.11):
With uv installed, run uv init --python 3.12 first if you're starting a new project.
uv add browser-use
2. Add your OpenAI API key to .env:
# .env
OPENAI_API_KEY=your-key
# BROWSER_USE_API_KEY=your-key # Optional: BU2 model or cloud browser
For either optional Browser Use service, get a Browser Use API key.
3. Save this as agent.py:
import asyncio
from browser_use import Agent, Browser, ChatBrowserUse, ChatOpenAI
from dotenv import load_dotenv
load_dotenv()
async def main():
llm = ChatOpenAI(model='gpt-5.6-luna', reasoning_effort='xhigh')
# llm = ChatBrowserUse(model='bu-2-0') # Use BU2 instead; requires BROWSER_USE_API_KEY
agent = Agent(
task="Find the number of stars of the browser-use repo",
llm=llm,
# browser=Browser(use_cloud=True), # Use a cloud browser; requires BROWSER_USE_API_KEY
)
history = await agent.run()
print(history.final_result())
if __name__ == "__main__":
asyncio.run(main())
To use BU2, replace the ChatOpenAI line with the commented ChatBrowserUse line. The cloud-browser option works with either model.
4. Run it:
uv run agent.py
The agent opens a browser, looks up the repository, and prints its answer.
Browser Use toolsets for Claude
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