OpenBrowser

Automating Walmart Product Scraping:

OpenbrowserAI-Top40Walmart.mp4

OpenBrowserAI Automatic Flight Booking:

OpenBrowserAI.-.Automatic.Flight.Booking.mp4

AI-powered browser automation using LangGraph and CDP (Chrome DevTools Protocol)

OpenBrowser is a framework for intelligent browser automation. It combines direct CDP communication with LangGraph orchestration to create AI agents that can navigate, interact with, and extract information from web pages autonomously.

Documentation

Full documentation: https://docs.openbrowser.me

Key Features

• LangGraph-Powered Agents - Stateful workflow orchestration with perceive-plan-execute loop
• Raw CDP Communication - Direct Chrome DevTools Protocol for maximum control and speed
• Vision Support - Screenshot analysis for visual understanding of pages
• 12+ LLM Providers - OpenAI, Anthropic, Google, Groq, AWS Bedrock, Azure OpenAI, Ollama, and more
• Code Agent Mode - Jupyter notebook-like code execution for complex automation
• MCP Server - Model Context Protocol support for Claude Desktop integration
• Video Recording - Record browser sessions as video files

Installation

pip install openbrowser-ai

With Optional Dependencies

# Install with all LLM providers
pip install openbrowser-ai[all]

# Install specific providers
pip install openbrowser-ai[anthropic]  # Anthropic Claude
pip install openbrowser-ai[groq]       # Groq
pip install openbrowser-ai[ollama]     # Ollama (local models)
pip install openbrowser-ai[aws]        # AWS Bedrock
pip install openbrowser-ai[azure]      # Azure OpenAI

# Install with video recording support
pip install openbrowser-ai[video]

Install Browser

uvx openbrowser install
# or
playwright install chromium

Quick Start

Basic Usage

import asyncio
from openbrowser import Agent, ChatGoogle

async def main():
    agent = Agent(
        task="Go to google.com and search for 'Python tutorials'",
        llm=ChatGoogle(),
    )
    
    result = await agent.run()
    print(f"Result: {result}")

asyncio.run(main())

With Different LLM Providers

from openbrowser import Agent, ChatOpenAI, ChatAnthropic, ChatGoogle

# OpenAI
agent = Agent(task="...", llm=ChatOpenAI(model="gpt-4o"))

# Anthropic
agent = Agent(task="...", llm=ChatAnthropic(model="claude-sonnet-4-0"))

# Google Gemini
agent = Agent(task="...", llm=ChatGoogle(model="gemini-2.0-flash"))

Using Browser Session Directly

import asyncio
from openbrowser import BrowserSession, BrowserProfile

async def main():
    profile = BrowserProfile(
        headless=True,
        viewport_width=1920,
        viewport_height=1080,
    )
    
    session = BrowserSession(browser_profile=profile)
    await session.start()
    
    await session.navigate_to("https://example.com")
    screenshot = await session.screenshot()
    
    await session.stop()

asyncio.run(main())

Configuration

Environment Variables

# Google (recommended)
export GOOGLE_API_KEY="..."

# OpenAI
export OPENAI_API_KEY="sk-..."

# Anthropic
export ANTHROPIC_API_KEY="sk-ant-..."

# Groq
export GROQ_API_KEY="gsk_..."

# AWS Bedrock
export AWS_ACCESS_KEY_ID="..."
export AWS_SECRET_ACCESS_KEY="..."
export AWS_DEFAULT_REGION="us-west-2"

# Azure OpenAI
export AZURE_OPENAI_API_KEY="..."
export AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"

# Browser-Use LLM (external service)
export BROWSER_USE_API_KEY="..."

BrowserProfile Options

from openbrowser import BrowserProfile

profile = BrowserProfile(
    headless=True,
    viewport_width=1280,
    viewport_height=720,
    disable_security=False,
    extra_chromium_args=["--disable-gpu"],
    record_video_dir="./recordings",
    proxy={
        "server": "http://proxy.example.com:8080",
        "username": "user",
        "password": "pass",
    },
)

Supported LLM Providers

Provider	Class	Models
Google	ChatGoogle	gemini-2.0-flash, gemini-1.5-pro
OpenAI	ChatOpenAI	gpt-4o, o3, gpt-4-turbo
Anthropic	ChatAnthropic	claude-sonnet-4-0, claude-3-opus
Groq	ChatGroq	llama-3.3-70b-versatile, mixtral-8x7b
AWS Bedrock	ChatAWSBedrock	claude-3, amazon.titan
Azure OpenAI	ChatAzureOpenAI	Any Azure-deployed model
Ollama	ChatOllama	llama3, mistral (local)
OCI	ChatOCIRaw	Oracle Cloud GenAI models
Browser-Use	ChatBrowserUse	External LLM service

MCP Server (Claude Desktop Integration)

OpenBrowser includes an MCP server for integration with Claude Desktop.

Running the MCP Server

python -m openbrowser.mcp

Claude Desktop Configuration

Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "openbrowser": {
      "command": "uvx",
      "args": ["openbrowser-ai", "mcp"],
      "env": {
        "GOOGLE_API_KEY": "..."
      }
    }
  }
}

CLI Usage

# Run a browser automation task
uvx openbrowser run "Search for Python tutorials on Google"

# Install browser
uvx openbrowser install

# Run MCP server
uvx openbrowser mcp

Project Structure

openbrowser-ai/
├── src/openbrowser/
│   ├── __init__.py          # Main exports
│   ├── cli.py                # CLI commands
│   ├── config.py             # Configuration
│   ├── actor/                # Element interaction
│   ├── agent/                # LangGraph agent
│   │   ├── graph.py          # Agent workflow
│   │   ├── service.py        # Agent class
│   │   └── views.py          # Data models
│   ├── browser/              # CDP browser control
│   │   ├── session.py        # BrowserSession
│   │   └── profile.py        # BrowserProfile
│   ├── code_use/             # Code agent
│   ├── dom/                  # DOM extraction
│   ├── llm/                  # LLM providers
│   │   ├── openai/
│   │   ├── anthropic/
│   │   ├── google/
│   │   ├── groq/
│   │   ├── aws/
│   │   ├── azure/
│   │   └── ...
│   ├── mcp/                  # MCP server
│   └── tools/                # Action registry
└── tests/                    # Test suite

Testing

# Run tests
pytest tests/

# Run with verbose output
pytest tests/ -v

Contributing

Contributions are welcome! Please:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact

• Email: billy.suharno@gmail.com
• GitHub: @billy-enrizky
• Repository: github.com/billy-enrizky/openbrowser-ai
• Documentation: https://docs.openbrowser.me

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Made with love for the AI automation community