agent-browser-clawdbot-bak-2026-01-28t18-01-09-10-30Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection
Install via ClawdBot CLI:
clawdbot install nicoataiza/agent-browser-clawdbot-bak-2026-01-28t18-01-09-10-30Fast browser automation using accessibility tree snapshots with refs for deterministic element selection.
Use agent-browser when:
Use built-in browser tool when:
# 1. Navigate and snapshot
agent-browser open https://example.com
agent-browser snapshot -i --json
# 2. Parse refs from JSON, then interact
agent-browser click @e2
agent-browser fill @e3 "text"
# 3. Re-snapshot after page changes
agent-browser snapshot -i --jsonagent-browser open <url>
agent-browser back | forward | reload | closeagent-browser snapshot -i --json # Interactive elements, JSON output
agent-browser snapshot -i -c -d 5 --json # + compact, depth limit
agent-browser snapshot -s "#main" -i # Scope to selectoragent-browser click @e2
agent-browser fill @e3 "text"
agent-browser type @e3 "text"
agent-browser hover @e4
agent-browser check @e5 | uncheck @e5
agent-browser select @e6 "value"
agent-browser press "Enter"
agent-browser scroll down 500
agent-browser drag @e7 @e8agent-browser get text @e1 --json
agent-browser get html @e2 --json
agent-browser get value @e3 --json
agent-browser get attr @e4 "href" --json
agent-browser get title --json
agent-browser get url --json
agent-browser get count ".item" --jsonagent-browser is visible @e2 --json
agent-browser is enabled @e3 --json
agent-browser is checked @e4 --jsonagent-browser wait @e2 # Wait for element
agent-browser wait 1000 # Wait ms
agent-browser wait --text "Welcome" # Wait for text
agent-browser wait --url "**/dashboard" # Wait for URL
agent-browser wait --load networkidle # Wait for network
agent-browser wait --fn "window.ready === true"agent-browser --session admin open site.com
agent-browser --session user open site.com
agent-browser session list
# Or via env: AGENT_BROWSER_SESSION=admin agent-browser ...agent-browser state save auth.json # Save cookies/storage
agent-browser state load auth.json # Load (skip login)agent-browser screenshot page.png
agent-browser screenshot --full page.png
agent-browser pdf page.pdfagent-browser network route "**/ads/*" --abort # Block
agent-browser network route "**/api/*" --body '{"x":1}' # Mock
agent-browser network requests --filter api # Viewagent-browser cookies # Get all
agent-browser cookies set name value
agent-browser storage local key # Get localStorage
agent-browser storage local set key valagent-browser tab new https://example.com
agent-browser tab 2 # Switch to tab
agent-browser frame @e5 # Switch to iframe
agent-browser frame main # Back to main{
"success": true,
"data": {
"snapshot": "...",
"refs": {
"e1": {"role": "heading", "name": "Example Domain"},
"e2": {"role": "button", "name": "Submit"},
"e3": {"role": "textbox", "name": "Email"}
}
}
}-i flag - Focus on interactive elements--json - Easier to parseagent-browser wait --load networkidlestate save/load--headed for debugging - See what's happeningagent-browser open https://www.google.com
agent-browser snapshot -i --json
# AI identifies search box @e1
agent-browser fill @e1 "AI agents"
agent-browser press Enter
agent-browser wait --load networkidle
agent-browser snapshot -i --json
# AI identifies result refs
agent-browser get text @e3 --json
agent-browser get attr @e4 "href" --json# Admin session
agent-browser --session admin open app.com
agent-browser --session admin state load admin-auth.json
agent-browser --session admin snapshot -i --json
# User session (simultaneous)
agent-browser --session user open app.com
agent-browser --session user state load user-auth.json
agent-browser --session user snapshot -i --jsonnpm install -g agent-browser
agent-browser install # Download Chromium
agent-browser install --with-deps # Linux: + system depsSkill created by Yossi Elkrief (@MaTriXy)
agent-browser CLI by Vercel Labs
Generated Mar 1, 2026
Use agent-browser to navigate e-commerce sites, log in with saved state, and extract product prices and availability from dynamic pages using ref-based element selection. This enables real-time tracking for competitive analysis without manual intervention.
Leverage session isolation to manage multiple social media accounts simultaneously, automating posts, interactions, and data extraction. The tool's deterministic element selection ensures reliable performance across complex single-page applications.
Implement end-to-end testing for web apps by simulating user workflows, such as form submissions and navigation, with ref-based clicks and waits. Use network control to mock APIs and validate responses, ensuring robust testing in isolated sessions.
Automate access to banking or financial portals by loading saved authentication states, then scrape transaction data and account balances from secure, dynamic interfaces. The tool's performance optimization handles complex SPAs efficiently for timely reporting.
Deploy agent-browser to scan websites for compliance with regulations, such as checking for required disclosures or inappropriate content. Use snapshot analysis and text extraction to automate reviews across multiple pages with session isolation.
Offer a cloud-based service where users schedule and run agent-browser scripts for tasks like monitoring, testing, or data extraction. Charge subscription fees based on usage tiers, with added value through analytics and integrations.
Provide bespoke automation solutions for enterprises, developing tailored agent-browser workflows for specific use cases like e-commerce or testing. Revenue comes from project-based fees and ongoing maintenance contracts.
Use agent-browser to collect and aggregate web data at scale, such as pricing or market trends, and sell processed datasets or APIs to clients. Monetize through data licensing and API access fees.
💬 Integration Tip
Integrate agent-browser into existing CI/CD pipelines for automated testing, using its JSON output for easy parsing and session management to run parallel tests efficiently.
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Headless browser automation CLI optimized for AI agents with accessibility tree snapshots and ref-based element selection