agent-browserA fast Rust-based headless browser automation CLI with Node.js fallback that enables AI agents to navigate, click, type, and snapshot pages via structured commands.
Install via ClawdBot CLI:
clawdbot install TheSethRose/agent-browserRequires:
npm install -g agent-browser
agent-browser install
agent-browser install --with-depsgit clone https://github.com/vercel-labs/agent-browser
cd agent-browser
pnpm install
pnpm build
agent-browser installagent-browser open <url> # Navigate to page
agent-browser snapshot -i # Get interactive elements with refs
agent-browser click @e1 # Click element by ref
agent-browser fill @e2 "text" # Fill input by ref
agent-browser close # Close browseragent-browser open agent-browser snapshot -i (returns elements with refs like @e1, @e2)agent-browser open <url> # Navigate to URL
agent-browser back # Go back
agent-browser forward # Go forward
agent-browser reload # Reload page
agent-browser close # Close browseragent-browser snapshot # Full accessibility tree
agent-browser snapshot -i # Interactive elements only (recommended)
agent-browser snapshot -c # Compact output
agent-browser snapshot -d 3 # Limit depth to 3
agent-browser snapshot -s "#main" # Scope to CSS selectoragent-browser click @e1 # Click
agent-browser dblclick @e1 # Double-click
agent-browser focus @e1 # Focus element
agent-browser fill @e2 "text" # Clear and type
agent-browser type @e2 "text" # Type without clearing
agent-browser press Enter # Press key
agent-browser press Control+a # Key combination
agent-browser keydown Shift # Hold key down
agent-browser keyup Shift # Release key
agent-browser hover @e1 # Hover
agent-browser check @e1 # Check checkbox
agent-browser uncheck @e1 # Uncheck checkbox
agent-browser select @e1 "value" # Select dropdown
agent-browser scroll down 500 # Scroll page
agent-browser scrollintoview @e1 # Scroll element into view
agent-browser drag @e1 @e2 # Drag and drop
agent-browser upload @e1 file.pdf # Upload filesagent-browser get text @e1 # Get element text
agent-browser get html @e1 # Get innerHTML
agent-browser get value @e1 # Get input value
agent-browser get attr @e1 href # Get attribute
agent-browser get title # Get page title
agent-browser get url # Get current URL
agent-browser get count ".item" # Count matching elements
agent-browser get box @e1 # Get bounding boxagent-browser is visible @e1 # Check if visible
agent-browser is enabled @e1 # Check if enabled
agent-browser is checked @e1 # Check if checkedagent-browser screenshot # Screenshot to stdout
agent-browser screenshot path.png # Save to file
agent-browser screenshot --full # Full page
agent-browser pdf output.pdf # Save as PDFagent-browser record start ./demo.webm # Start recording (uses current URL + state)
agent-browser click @e1 # Perform actions
agent-browser record stop # Stop and save video
agent-browser record restart ./take2.webm # Stop current + start new recordingRecording creates a fresh context but preserves cookies/storage from your session. If no URL is provided, it automatically returns to your current page. For smooth demos, explore first, then start recording.
agent-browser wait @e1 # Wait for element
agent-browser wait 2000 # Wait milliseconds
agent-browser wait --text "Success" # Wait for text
agent-browser wait --url "/dashboard" # Wait for URL pattern
agent-browser wait --load networkidle # Wait for network idle
agent-browser wait --fn "window.ready" # Wait for JS conditionagent-browser mouse move 100 200 # Move mouse
agent-browser mouse down left # Press button
agent-browser mouse up left # Release button
agent-browser mouse wheel 100 # Scroll wheelagent-browser find role button click --name "Submit"
agent-browser find text "Sign In" click
agent-browser find label "Email" fill "user@test.com"
agent-browser find first ".item" click
agent-browser find nth 2 "a" textagent-browser set viewport 1920 1080 # Set viewport size
agent-browser set device "iPhone 14" # Emulate device
agent-browser set geo 37.7749 -122.4194 # Set geolocation
agent-browser set offline on # Toggle offline mode
agent-browser set headers '{"X-Key":"v"}' # Extra HTTP headers
agent-browser set credentials user pass # HTTP basic auth
agent-browser set media dark # Emulate color schemeagent-browser cookies # Get all cookies
agent-browser cookies set name value # Set cookie
agent-browser cookies clear # Clear cookies
agent-browser storage local # Get all localStorage
agent-browser storage local key # Get specific key
agent-browser storage local set k v # Set value
agent-browser storage local clear # Clear allagent-browser network route <url> # Intercept requests
agent-browser network route <url> --abort # Block requests
agent-browser network route <url> --body '{}' # Mock response
agent-browser network unroute [url] # Remove routes
agent-browser network requests # View tracked requests
agent-browser network requests --filter api # Filter requestsagent-browser tab # List tabs
agent-browser tab new [url] # New tab
agent-browser tab 2 # Switch to tab
agent-browser tab close # Close tab
agent-browser window new # New windowagent-browser frame "#iframe" # Switch to iframe
agent-browser frame main # Back to main frameagent-browser dialog accept [text] # Accept dialog
agent-browser dialog dismiss # Dismiss dialogagent-browser eval "document.title" # Run JavaScriptagent-browser state save auth.json # Save session state
agent-browser state load auth.json # Load saved stateagent-browser open https://example.com/form
agent-browser snapshot -i
# Output shows: textbox "Email" [ref=e1], textbox "Password" [ref=e2], button "Submit" [ref=e3]
agent-browser fill @e1 "user@example.com"
agent-browser fill @e2 "password123"
agent-browser click @e3
agent-browser wait --load networkidle
agent-browser snapshot -i # Check result# Login once
agent-browser open https://app.example.com/login
agent-browser snapshot -i
agent-browser fill @e1 "username"
agent-browser fill @e2 "password"
agent-browser click @e3
agent-browser wait --url "/dashboard"
agent-browser state save auth.json
# Later sessions: load saved state
agent-browser state load auth.json
agent-browser open https://app.example.com/dashboardagent-browser --session test1 open site-a.com
agent-browser --session test2 open site-b.com
agent-browser session listAdd --json for machine-readable output:
agent-browser snapshot -i --json
agent-browser get text @e1 --jsonagent-browser open example.com --headed # Show browser window
agent-browser console # View console messages
agent-browser console --clear # Clear console
agent-browser errors # View page errors
agent-browser errors --clear # Clear errors
agent-browser highlight @e1 # Highlight element
agent-browser trace start # Start recording trace
agent-browser trace stop trace.zip # Stop and save trace
agent-browser record start ./debug.webm # Record from current page
agent-browser record stop # Save recording
agent-browser --cdp 9222 snapshot # Connect via CDPGenerated Feb 24, 2026
QA teams can use agent-browser to automate functional and regression testing of web applications. It enables scripted interactions like clicking buttons, filling forms, and validating page states, reducing manual testing effort and improving test coverage.
Market research firms can automate the collection of structured data from websites, such as product prices, reviews, or competitor information. The tool's snapshot and interaction capabilities allow for navigating paginated content and extracting data efficiently.
Organizations can automate repetitive web-based administrative tasks, such as filling out online forms for applications, registrations, or data entry. This saves time and reduces human error in processes like HR onboarding or compliance reporting.
Web developers and auditors can use agent-browser to programmatically check web pages for accessibility issues. By analyzing interactive elements and page structures, it helps identify compliance gaps with standards like WCAG.
Educators and trainers can create automated video demos of web applications for tutorials or documentation. The recording feature captures interactions step-by-step, making it easy to produce engaging instructional content.
Offer a cloud-based service where users can schedule and run agent-browser scripts for tasks like monitoring, testing, or data scraping. Charge subscription fees based on usage tiers, such as number of scripts or execution time.
Provide consulting services to help businesses integrate agent-browser into their workflows for automation projects. Revenue comes from custom development, training, and ongoing support contracts tailored to client needs.
Distribute agent-browser as a free open-source tool with basic features, while offering premium add-ons like advanced analytics, team collaboration, or priority support. Monetize through one-time purchases or tiered subscriptions.
💬 Integration Tip
Integrate agent-browser into CI/CD pipelines for automated testing, using its CLI commands in scripts to run tests on every code commit.
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