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Browser Use
Browser Use is a browser automation framework for AI agents that can navigate websites, click elements, type into pages, use custom tools, and run browser tasks through code or CLI workflows.
Use its Python library in your application, give an existing agent browser access through the CLI, or send tasks to the fully hosted API. A cloud browser and a hosted agent are separate choices. Use this as a first read, not a recommendation. Open the original project before trusting details like terms, limits, privacy, cost, setup, or safety.
What it is
A browser-control layer for agents
Supply a task and model to the Python agent, which can read page state, choose clicks or typing, call custom tools and return a run history and final result.
Why it stands out
Choose who runs the agent and browser
The fully hosted API runs both. The CLI gives your existing agent browser control, while the Python library lets your application supply the model and tools. Either of those two paths can use a local or cloud browser.
Availability
Code and managed services
The project declares the Python library MIT-licensed and documents Python 3.11 or newer. Model-provider usage and managed browser or agent services are separate parts of the setup.
Why it matters
What makes it useful
Finding an available appointment or collecting information across websites may involve forms and page controls rather than one API request. Browser Use gives an agent page state and browser actions for that kind of task, with custom tools for actions your application exposes.
What to know
Where it fits
Choose the Python library when your application needs to supply the model, tools and output format. Give it a task, connect a local or cloud browser, run the agent and inspect its history or final result. The CLI instead adds browser access to an existing agent; the hosted API runs the agent as well as the browser.
Notable points
What stands out
The browser profile can be chosen separately from the agent. The documented local path can reuse a Chrome profile. Current Cloud profile documentation describes syncing cookies and local storage. A profile ID belongs to the project that created it, and login state can expire, so a synced profile may still need another sign-in.
Before using
What to review
A signed-in browser profile exposes account access to the run. Start with a test account and decide which submissions, purchases or account changes need your own approval.
Check that the website permits the task and your chosen automation method, including its current terms and your permission to use the account. Account access alone does not settle those questions.
Check model-provider and cloud-service data handling, screenshots, saved conversations and file access. A locally running browser does not make a remote model request local.
Review model and hosted-service usage costs separately from the Python library. The repository declares the library MIT-licensed; check its main source and the current service terms for your intended setup.
The published GHSA-x39x-9qw5-ghrf advisory describes an allowed_domains bypass in versions up to 0.1.44 and lists 0.1.45 as patched. That historical fix does not establish that every navigation or account action is protected.
For a browser created through the Cloud browser API, closing a client or disconnecting its remote-control connection does not stop the managed browser. The current SDK examples call client.browsers.stop(session.id) when finished.
Reader fit
Who may find it relevant
Python builders who need custom tools and structured results around website tasks.
Teams choosing between browser access for an existing agent and a hosted service that runs the agent too.
Less relevant for readers seeking a model checkpoint or a finished consumer assistant. Local browser execution alone does not establish an offline workflow.
Editorial note
Why LifeHubber lists it
Browser Use is useful when an application needs a task-specific rule alongside the agent instructions it already uses. Its additive prompt parameter provides a way to include that rule without replacing the default prompt. Decide whether a custom instruction should add to or replace the agent's built-in prompt. Put the objective in task=. The documented extend_system_message parameter adds instructions; override_system_message replaces the default prompt completely. Choose the additive parameter when you need an extra instruction while keeping the default prompt.
Source links
Source materials
Reader note
Before relying on this entry
LifeHubber lists entries to help readers inspect AI projects, not to endorse them or prove they are safe, suitable, accurate, maintained, or right for a specific use. We do not verify every entry in depth. Before relying on anything listed, review the original materials, terms, privacy practices, limits, and risks that matter for your situation.
What to explore next
Set the browser boundary before scaling the task.
A browser agent can work across sites, accounts, forms, and logged-in sessions. Compare a narrower in-page design, then set the approvals and stop points before real actions are involved.
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