
browser-use
🌐 Make websites accessible for AI agents. Automate tasks online with ease.
Stars: 69802

Browser Use is a tool designed to make websites accessible for AI agents. It provides an easy way to connect AI agents with the browser, enabling users to perform tasks such as extracting vision and HTML elements, managing multiple tabs, and executing custom actions. The tool supports various language models and allows users to parallelize multiple agents for efficient processing. With features like self-correction and the ability to register custom actions, Browser Use offers a versatile solution for interacting with web content using AI technology.
README:
Deutsch | Español | français | 日本語 | 한국어 | Português | Русский | 中文
🌤️ Want to skip the setup? Use our cloud for faster, scalable, stealth-enabled browser automation!
🚀 Use the latest version!
We ship every day improvements for speed, accuracy, and UX.
uv pip install --upgrade browser-use
With uv (Python>=3.11):
uv pip install browser-use
If you don't already have Chrome or Chromium installed, you can also download the latest Chromium using playwright's install shortcut:
uvx playwright install chromium --with-deps --no-shell
Spin up your agent:
import asyncio
from dotenv import load_dotenv
load_dotenv()
from browser_use import Agent, ChatOpenAI
async def main():
agent = Agent(
task="Find the number of stars of the browser-use repo",
llm=ChatOpenAI(model="gpt-4.1-mini"),
)
await agent.run()
asyncio.run(main())
Add your API keys for the provider you want to use to your .env
file.
OPENAI_API_KEY=
For other settings, models, and more, check out the documentation 📕.
Task: Add grocery items to cart, and checkout.
Prompt: Add my latest LinkedIn follower to my leads in Salesforce.
Prompt: Read my CV & find ML jobs, save them to a file, and then start applying for them in new tabs, if you need help, ask me.'
https://github.com/user-attachments/assets/171fb4d6-0355-46f2-863e-edb04a828d04
Prompt: Write a letter in Google Docs to my Papa, thanking him for everything, and save the document as a PDF.
Prompt: Look up models with a license of cc-by-sa-4.0 and sort by most likes on Hugging face, save top 5 to file.
https://github.com/user-attachments/assets/de73ee39-432c-4b97-b4e8-939fd7f323b3
For more examples see the examples folder or join the Discord and show off your project. You can also see our awesome-prompts
repo for prompting inspiration.
Browser-use supports the Model Context Protocol (MCP), enabling integration with Claude Desktop and other MCP-compatible clients.
Add browser-use to your Claude Desktop configuration:
{
"mcpServers": {
"browser-use": {
"command": "uvx",
"args": ["browser-use[cli]", "--mcp"],
"env": {
"OPENAI_API_KEY": "sk-..."
}
}
}
}
This gives Claude Desktop access to browser automation tools for web scraping, form filling, and more.
Browser-use agents can connect to multiple external MCP servers to extend their capabilities:
import asyncio
from browser_use import Agent, Tools, ChatOpenAI
from browser_use.mcp.client import MCPClient
async def main():
# Initialize tools
tools = Tools()
# Connect to multiple MCP servers
filesystem_client = MCPClient(
server_name="filesystem",
command="npx",
args=["-y", "@modelcontextprotocol/server-filesystem", "/Users/me/documents"]
)
github_client = MCPClient(
server_name="github",
command="npx",
args=["-y", "@modelcontextprotocol/server-github"],
env={"GITHUB_TOKEN": "your-github-token"}
)
# Connect and register tools from both servers
await filesystem_client.connect()
await filesystem_client.register_to_tools(tools)
await github_client.connect()
await github_client.register_to_tools(tools)
# Create agent with MCP-enabled tools
agent = Agent(
task="Find the latest pdf report in my documents and create a GitHub issue about it",
llm=ChatOpenAI(model="gpt-4.1-mini"),
tools=tools # Tools has tools from both MCP servers
)
# Run the agent
await agent.run()
# Cleanup
await filesystem_client.disconnect()
await github_client.disconnect()
asyncio.run(main())
See the MCP documentation for more details.
Tell your computer what to do, and it gets it done.
- [ ] Make agent 3x faster
- [ ] Reduce token consumption (system prompt, DOM state)
- [ ] Enable interaction with all UI elements
- [ ] Improve state representation for UI elements so that any LLM can understand what's on the page
- [ ] Let user record a workflow - which we can rerun with browser-use as a fallback
- [ ] Create various templates for tutorial execution, job application, QA testing, social media, etc. which users can just copy & paste.
- [ ] Human work is sequential. The real power of a browser agent comes into reality if we can parallelize similar tasks. For example, if you want to find contact information for 100 companies, this can all be done in parallel and reported back to a main agent, which processes the results and kicks off parallel subtasks again.
We love contributions! Feel free to open issues for bugs or feature requests. To contribute to the docs, check out the /docs
folder.
We offer to run your tasks in our CI—automatically, on every update!
-
Add your task: Add a YAML file in
tests/agent_tasks/
(see theREADME there
for details). - Automatic validation: Every time we push updates, your task will be run by the agent and evaluated using your criteria.
To learn more about the library, check out the local setup 📕.
main
is the primary development branch with frequent changes. For production use, install a stable versioned release instead.
Want to show off your Browser-use swag? Check out our Merch store. Good contributors will receive swag for free 👀.
If you use Browser Use in your research or project, please cite:
@software{browser_use2024,
author = {Müller, Magnus and Žunič, Gregor},
title = {Browser Use: Enable AI to control your browser},
year = {2024},
publisher = {GitHub},
url = {https://github.com/browser-use/browser-use}
}
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