Browser Use: An open-source AI agent to automate web-based tasks

Author’s note: The generative AI revolution has sparked an explosion of open-source tools that fundamentally transform how developers build and deploy AI-powered applications. Each month here, I will introduce an innovative new project from the open-source AI ecosystem, providing an overview of the project along with some tips to help you harness its capabilities.

Project overview – Browser Use

Browser Use is an open-source project created by Magnus Muller and Gregor Zunic to make websites accessible to AI agents. As of January 2025, the project’s GitHub repository boasts over 21,000 stars and 51 contributors, reflecting its growing popularity in the AI automation landscape.

While APIs are the preferred mechanism for integrating external applications with AI agents, web browser automation plays an important role in digital interactions. Browser Use connects AI agents directly to web browsers, enabling them to autonomously navigate, interact with, and extract information from websites—effectively bridging the gap between artificial intelligence and web browsing. This is useful for developers seeking to create intelligent, web-native agents that can perform tasks ranging from data collection to complex multi-step workflows.

What problem does Browser Use solve?

Web automation and browser interaction have long been challenging for developers and AI researchers. Traditional tools like Selenium struggle with dynamic web elements, complex user interactions, and maintaining test stability across different browser environments.

Existing web automation frameworks are typically rigid, requiring extensive coding expertise and constant maintenance, which creates significant overhead for development teams.

The current landscape of browser automation is fragmented and inefficient. Developers face multiple pain points:

Managing dynamic web content that changes quickly

Ensuring cross-browser compatibility

Developing reliable interaction scripts

Maintaining test suites as web applications evolve

AI agents attempting web interactions encounter even more complex challenges. Most existing solutions lack the flexibility to autonomously navigate websites, interpret complex UI elements, and perform multi-step tasks without breaking. The WebArena leaderboard reveals that even the best-performing AI models have a success rate of only 35.8% when attempting real-world web tasks.

These limitations particularly impact developers, AI researchers, and automation engineers. Startups and enterprises seeking to build intelligent web-browsing agents are constrained by current technological barriers and unable to create robust, adaptable solutions that can reliably interact with diverse web environments.

A closer look at Browser Use

Browser Use is an open-source library designed to empower AI agents with seamless web browsing capabilities for Python developers. It provides a robust framework that enables AI to interact with websites dynamically, mimicking human-like browsing behavior across different programming ecosystems.

At the heart of Browser Use’s browser automation is Playwright, a powerful cross-browser automation library developed by Microsoft. Playwright enables reliable, fast web automation by providing a unified API for Chromium, Firefox, and WebKit browsers. It offers advanced features like automatic waiting, network interception, and robust selector engines, which Browser Use leverages to create more intelligent and resilient web interaction agents.

Browser Use relies heavily on Chromium to perform its tasks. I couldn’t find a way to change this behavior to utilize an existing browser on my machine.

The project supports multiple models:

OpenAI’s GPT models

Google Gemini

Azure OpenAI

Anthropic Claude

DeepSeek

Ollama

Browser Use distinguishes itself through several unique features:

Integration with multiple large language models (LLMs)

Persistent browser sessions

Complex workflow management

Intelligent DOM interaction

The library integrates smoothly with:

LangChain for AI workflow management

Playwright for cross-browser automation

Major AI development platforms

Browser Use employs a hierarchical agent architecture featuring:

A planner agent for task decomposition

A browser navigation agent for web interactions

Flexible skills for web page sensing and acting

By leveraging LangChain, Browser Use taps into the wide range of LLM support already provided by the popular framework.

One limitation I encountered while exploring the framework is its lack of integration with mainstream agent frameworks such as CrewAI, AutoGen, and PhiData. Consequently, I had to develop a custom tool and register it with the agent—not a straightforward process, as I needed to understand the JSON schema of the output and carefully extract the final content.

Key use cases for Browser Use

1. Web research and data extraction: Browser Use enables AI agents to autonomously navigate complex websites, extract structured information, and perform comprehensive research tasks. For instance, an AI agent can:

Automatically search job boards and compile detailed job listings

Scrape product information across multiple e-commerce platforms

Gather competitive intelligence by analyzing websites in real-time

2. Workflow automation:
 The library allows AI agents to interact with web interfaces just like humans, automating multi-step processes such as:

Filling out online forms

Booking travel reservations

Tracking package deliveries

Managing account registrations and updates

3. Cross-platform integration:
 Browser Use supports seamless integration with multiple LLMs and frameworks, enabling developers to build sophisticated web-interacting agents across various domains.

I tried out Browser Use with GPT-4o by attempting to bypass the BotDetect CAPTCHA demo (shown below), achieving a 75% success rate.

IDG

Harnessing AI agents for browser automation

Browser Use represents a pivotal innovation in AI agent development. It addresses critical challenges in web automation and browser interaction. By providing an open-source framework that enables AI agents to navigate websites dynamically, the project fills a significant gap in current web automation technologies.

The project thrives on community collaboration, welcoming contributions from developers worldwide. With an active GitHub community and open issues, Browser Use encourages developers to participate in expanding its capabilities. The project’s transparent development approach and MIT licensing make it accessible for both individual developers and enterprise teams.

While Browser Use is an open-source library for AI-driven browser automation, one of the commercial alternatives is BrowserBase. BrowserBase offers headless browser infrastructure for web automation. It distinguishes itself with features like advanced debugging, session recording, proxy support, and stealth mechanisms to avoid bot detection. Unlike Browser Use’s library approach, BrowserBase offers a complete infrastructure platform for running headless browsers, targeting enterprises needing scalable web automation solutions.

Bottom line – Browser Use

Browser Use stands out as a significant tool for developers seeking to integrate AI agents with web browsers. Its comprehensive features, ease of use, and active community support make it an asset in the realm of AI-driven web automation. By facilitating seamless AI-browser interactions, Browser Use contributes to the advancement of intelligent web-based applications.