Browser Use
Open-source Python library that lets LLM agents drive a real web browser
Overview
Browser Use is an MIT-licensed Python framework that puts an LLM in control of a real browser — navigating, clicking, typing, and extracting data from live pages. A hosted Cloud layer adds stealth browsers, proxies, and scheduled agent runs on top of the open-source core.
Pricing
Pricing shown for reference only. These figures reflect RECATOOLS research as of 21 Jul 2026 and may be out of date or incomplete. This is not financial or purchasing advice — always confirm the current price on the provider’s official website before making any decision.
- 3 concurrent sessions
- 1 team member, 1 browser profile
- Advanced stealth and captcha solving
- Webhook events, community support
- $29 in monthly credits
- 25 concurrent sessions
- 5 team members, 5 browser profiles
- Premium proxy pool, BYOK
- Scheduled jobs, priority support
- $299 in monthly credits
- 200 concurrent sessions
- Unlimited team members and browser profiles
- Premium proxy pool, BYOK
- Scheduled jobs, priority support
- $999 in monthly credits
- 500 concurrent sessions
- Unlimited team members and browser profiles
- Premium proxy pool, BYOK
- Scheduled jobs, dedicated support
- Annual credit pool
- SLAs and data retention terms
- Dedicated support
- Contact [email protected]
What you can produce with Browser Use
- An MIT-licensed Python library (pip install browser-use, Python 3.11+) that lets an LLM operate a real Chromium browser through the Chrome DevTools Protocol.
- A DOM-based page representation that hands the model clickable and typeable elements as structured data instead of screenshots.
- Support for bringing your own LLM — OpenAI, Anthropic, Google Gemini, and the project's hosted ChatBrowserUse models — via API key.
- Open-source sibling projects: workflow-use for recording deterministic replayable workflows and web-ui for running agents from a browser interface.
- A CLI and MCP server for wiring the agent into other tools and IDE assistants.
- Browser Use Cloud with hosted stealth browsers, captcha solving, a premium proxy pool, scheduled jobs, and a REST API, from a $0 plan upward.
- Weekly-or-faster releases from a Y Combinator-backed team that announced a $17M seed round in 2025.
ASEAN Perspective
Browser Use in Southeast Asia
ASEAN-region availability and pricing notes coming soon. Drop the editorial team a note via /contact/ if you can supply local context (Singapore/Malaysia/Indonesia/Thailand/Vietnam).
Think of Browser Use as an agent automation tool first and a scraper second. It's a Python library that gives an LLM control of a real Chromium browser through the Chrome DevTools Protocol, using the project's open-source Browser Harness. The model receives a structured view of the page's DOM and decides what to click, type, or extract next, which makes it suited to multi-step jobs a fixed script can't survive — form-filling across changing layouts, QA flows, agent research, and extraction from sites that resist selector-based scrapers. Sibling repos extend the core: workflow-use records deterministic, replayable workflows, and web-ui wraps the agent in a browser-based interface.
It is built for Python developers (3.11+) comfortable wiring up their own LLM keys — OpenAI, Anthropic, Gemini, and the project's own hosted models are all supported — and for teams who want the agent loop open and inspectable rather than locked inside a SaaS. The company behind it went through Y Combinator and announced a $17M seed round on its own blog in 2025, and ships at a pace that suits early adopters better than teams needing a frozen API.
The library is free under MIT (pip install browser-use), with the cost of runs set by your LLM bill. Browser Use Cloud is the paid layer: a $0 Free plan, then Dev at $29/month, Business at $299/month, Scaleup at $999/month, and custom Enterprise terms, adding stealth browsers, captcha solving, proxies, scheduled jobs, and usage-priced sessions at $0.02/hour.
What people say
Browser Use is the tool Python developers usually reach for when they need an LLM to operate a browser, and user sentiment reflects both the excitement and growing pains of that role. The DOM-first design earns consistent praise. Instead of making a vision model guess at screenshots, the library serialises the page's element tree into a structured list of what the model can click, type into, or read. In practice that makes runs faster, cheaper, and more precise than vision-only agents, and it can act on content that is off-screen or visually hidden. The pace of development draws almost as much comment as the product itself — releases land multiple times a week, new models are supported within days of launch, and the 0.13 line introduced a Rust-backed agent loop and the new Browser Harness after the project swapped Playwright for direct Chrome DevTools Protocol control.
The complaints are the familiar ones for agentic tooling. Reliability on complex sites is the loudest: issue threads describe forms that submit twice, confirmation screens that appear without the data actually recording, agents that wander off to click a Help link mid-task, and pages read before they finish loading. Token cost comes a close second — long multi-step runs feed a lot of DOM into the model, and GitHub discussions are full of tactics for trimming context or switching to cheaper models like Gemini Flash. The rapid cadence cuts both ways too: users report breaking changes between minor versions, and the Playwright-to-CDP migration meant real rework in downstream projects.
It's a useful, fast-moving library that rewards supervision. Deterministic scripts still win for stable, known workflows; where page layouts vary or the task needs judgment, this is one of the strongest open options available.
Summary of public user & expert reviews, compiled by RECATOOLS.
About this listing
This entry was compiled from publicly available data including Browser Use's official website, press releases, documentation, and reputable third-party publications. RECATOOLS is not affiliated with Browser Use unless explicitly stated.
Third-party AI tools update their pricing, features, availability, and policies frequently. Information here may be outdated by the time you read this — we make reasonable efforts to keep listings current, but cannot guarantee absolute accuracy.
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