
Agent Browser
- 152 installs
- 7 repo stars
- Updated January 15, 2026
- eyadsibai/ltk
Let coding agents drive a real browser to verify UI flows, scrape pages, file forms, and capture evidence during integration tasks.
About
agent-browser equips Claude Code agents with disciplined browser automation for development and validation tasks. It standardizes how agents open pages, interact with DOM elements, wait for network idle, capture screenshots, and return structured observations so web features can be exercised, debugged, or documented without manual clicking through every regression path.
- Headful or headless browser control for agents
- UI verification and end-to-end flow checks
- Structured page interaction and extraction
- Useful for QA-style agent loops
- From eyadsibai/ltk agent toolkit
Agent Browser by the numbers
- 152 all-time installs (skills.sh)
- Ranked #3,352 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
- Data as of Jul 30, 2026 (Skillselion catalog sync)
npx skills add https://github.com/eyadsibai/ltk --skill agent-browserAdd your badge
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| Installs | 152 |
|---|---|
| repo stars | ★ 7 |
| Last updated | January 15, 2026 |
| Repository | eyadsibai/ltk ↗ |
What it does
Let coding agents drive a real browser to verify UI flows, scrape pages, file forms, and capture evidence during integration tasks.
Files
agent-browser: CLI Browser Automation
Vercel's headless browser automation CLI designed for AI agents. Uses ref-based selection (@e1, @e2) from accessibility snapshots.
Setup
# Check installation
command -v agent-browser >/dev/null 2>&1 && echo "Installed" || echo "NOT INSTALLED"
# Install if needed
npm install -g agent-browser
agent-browser install # Downloads ChromiumCore Workflow
The snapshot + ref pattern is optimal for LLMs:
1. Navigate to URL 2. Snapshot to get interactive elements with refs 3. Interact using refs (@e1, @e2, etc.) 4. Re-snapshot after navigation or DOM changes
agent-browser open https://example.com
agent-browser snapshot -i # Get refs
agent-browser click @e1 # Use ref
agent-browser fill @e2 "text"
agent-browser snapshot -i # Re-snapshotKey Commands
Navigation
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 browserSnapshots (Essential for AI)
agent-browser snapshot # Full accessibility tree
agent-browser snapshot -i # Interactive elements only (recommended)
agent-browser snapshot -i --json # JSON output for parsing
agent-browser snapshot -c # Compact (remove empty)
agent-browser snapshot -d 3 # Limit depthInteractions
agent-browser click @e1 # Click element
agent-browser dblclick @e1 # Double-click
agent-browser fill @e1 "text" # Clear and fill input
agent-browser type @e1 "text" # Type without clearing
agent-browser press Enter # Press key
agent-browser hover @e1 # Hover element
agent-browser check @e1 # Check checkbox
agent-browser uncheck @e1 # Uncheck
agent-browser select @e1 "option" # Select dropdown
agent-browser scroll down 500 # Scroll
agent-browser scrollintoview @e1 # Scroll element into viewGet Information
agent-browser get text @e1 # Get element text
agent-browser get html @e1 # Get element HTML
agent-browser get value @e1 # Get input value
agent-browser get attr href @e1 # Get attribute
agent-browser get title # Get page title
agent-browser get url # Get current URLScreenshots & PDFs
agent-browser screenshot # Viewport screenshot
agent-browser screenshot --full # Full page
agent-browser screenshot output.png # Save to file
agent-browser pdf output.pdf # Save as PDFWait
agent-browser wait @e1 # Wait for element
agent-browser wait 2000 # Wait milliseconds
agent-browser wait "text" # Wait for textExamples
Login Flow
agent-browser open https://app.example.com/login
agent-browser snapshot -i
# Output: textbox "Email" [ref=e1], textbox "Password" [ref=e2], button "Sign in" [ref=e3]
agent-browser fill @e1 "user@example.com"
agent-browser fill @e2 "password123"
agent-browser click @e3
agent-browser wait 2000
agent-browser snapshot -i # Verify logged inForm Filling
agent-browser open https://forms.example.com
agent-browser snapshot -i
agent-browser fill @e1 "John Doe"
agent-browser fill @e2 "john@example.com"
agent-browser select @e3 "United States"
agent-browser check @e4 # Agree to terms
agent-browser click @e5 # Submit
agent-browser screenshot confirmation.pngDebug Mode (Visible Browser)
agent-browser --headed open https://example.com
agent-browser --headed snapshot -i
agent-browser --headed click @e1Sessions (Parallel Browsers)
agent-browser --session browser1 open https://site1.com
agent-browser --session browser2 open https://site2.com
agent-browser session listJSON Output
agent-browser snapshot -i --jsonReturns:
{
"success": true,
"data": {
"refs": {
"e1": {"name": "Submit", "role": "button"},
"e2": {"name": "Email", "role": "textbox"}
}
}
}When to Use vs Alternatives
Use agent-browser when:
- Prefer Bash-based workflows
- Need quick one-off automation
- Want simpler CLI commands
Use Playwright MCP when:
- Need deep MCP tool integration
- Building complex automation pipelines
- Want tool-based responses