Delv
BrowserActive· 6dby Browser Use★ 4.3

Browser Use

Open-source Python library for web-browsing AI agents that combines LLMs with HTML and visual analysis for robust automation.

Try it Source
B
Safety & Trust

Delv Safety Grade: B

Score 71/100 · assessed 2026-04-18

Maintainer55
Permissions35
Supply chain75
Transparency85
Incidents100

Browser Use is an open-source Python library enabling AI agents to control web browsers through both HTML parsing and visual analysis. The project demonstrates good transparency with active GitHub development, clear documentation, and standard PyPI distribution. However, it carries significant security implications: it provides unrestricted browser control including form filling, clicking, navigation, and JavaScript execution across arbitrary websites. The maintainer appears to be a smaller organisation or individual with moderate GitHub activity (launched late 2024). Supply chain is reasonable via PyPI with standard dependencies. The freemium model suggests commercial backing but the organisation's track record is limited. No known security incidents, but the broad browser automation capabilities require careful consideration of what sites and credentials you expose to AI agents using this library.

Green flags

  • Fully open source on GitHub with active development and issues
  • Standard PyPI distribution with versioned releases
  • Clear documentation and examples available
  • No known security incidents or malicious behaviour
  • Combines multiple interaction modes (HTML + vision) for robustness

Red flags

  • Full browser control including form submission and arbitrary site navigation
  • Can execute JavaScript and interact with sensitive web applications
  • Relatively new project (late 2024) with limited maintainer track record
  • Freemium model may pressure users toward paid cloud service
  • Visual analysis could capture sensitive on-screen information

Permissions requested

Browser controlOutbound networkRead filesExternal LLM callDesktop control
Assessed by Delv Editorial using public metadata. Grades are advisory and update as the ecosystem changes. They do not replace your own review of permissions and code before granting an agent access to sensitive systems.

Pricing

FREEMIUM — Free library, paid cloud

Platforms

apicli

Review

Browser Use is a Python library that hands your LLM the keys to a real browser. It combines Claude, GPT-4, or similar models with Playwright automation, feeding them both the HTML DOM and visual screenshots so the agent can click, scroll, and fill forms like a human would. The autonomy here is genuine: you give it a goal ("find the three cheapest flights to Berlin next week and save them to a spreadsheet"), and it plans, executes, and recovers from failures without you babysitting each step. I used it to scrape pricing data from a competitor's site that hid everything behind JavaScript dropdowns and a CAPTCHA-adjacent challenge. A standard scraper would have choked. Browser Use's vision model spotted the dropdowns, clicked through the filters, waited for lazy-loaded content, and extracted the tables. It took three attempts because the site's layout shifted mid-session, but the agent adapted without me writing error handlers. That resilience is the real win: it doesn't just execute a script, it observes and reacts. The library is open-source and runs locally, which matters if you're handling sensitive workflows. You bring your own LLM API key (OpenAI, Anthropic, or local models via LiteLLM), so costs scale with usage. The paid cloud version offers hosted execution and pre-built integrations, but the core library is free and surprisingly capable. Setup is straightforward if you're comfortable with Python and Playwright. Failure modes: it can burn tokens fast on complex sites, especially if the DOM is bloated. Vision analysis helps, but it's not infallible—I've seen it misidentify buttons when CSS styling is ambiguous. It also lacks memory across sessions by default, so multi-day research tasks need custom state management. Compared to something like Skyvern (which is more opinionated and workflow-focused), Browser Use is lower-level and more flexible, but you'll write more glue code. The documentation is solid, with examples for common patterns like form filling and data extraction. The repo is active, and the maintainers respond to issues quickly. If you need an agent that can handle the messy, interactive web—not just static APIs—this is one of the best tools available. Just budget for LLM costs and be ready to tune prompts for tricky sites.
Verdict

Pay for the cloud version if you need hosted execution or want to skip infrastructure setup. Stick with the free library if you're comfortable with Python and want full control. Skip it if your workflows are purely API-based or you need guaranteed determinism.

Good at

  • Combines HTML parsing and vision analysis for robust site navigation
  • Open-source library with no vendor lock-in, runs locally
  • Adapts to layout changes and recovers from failures mid-workflow
  • Supports multiple LLM providers including local models
  • Active development and responsive maintainers

Watch out

  • Token costs can escalate quickly on complex or bloated sites
  • Vision model occasionally misidentifies UI elements with ambiguous styling
  • No built-in session memory for multi-day workflows
  • Requires Python and Playwright knowledge for setup and customisation
  • Less opinionated than workflow-focused competitors, more glue code needed

Use cases

  • web automation
  • multi-step workflows
  • agent research