Visual UI Debug Agent MCP

Autonomous MCP Server for AI-Powered Visual UI Testing & Debugging
_{30 powerful tools for screenshots, workflows, performance, and visual analysis}

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What is VUDA?

VUDA (Visual UI Debug Agent) is an MCP (Model Context Protocol) server that gives AI models the power to visually analyze, test, and debug web interfaces using Playwright. It enables any AI - even those without built-in vision - to inspect web pages, find UI bugs, test user workflows, and measure performance autonomously.

Key Capabilities

• Visual Analysis - Capture screenshots, analyze page structure, map interactive elements
• Workflow Testing - Automatically test user journeys with step-by-step validation
• Performance Monitoring - Measure load times, analyze metrics, identify bottlenecks
• API Testing - Validate backend endpoints and responses
• Visual Comparison - Detect UI changes between versions with diff highlighting
• Console Monitoring - Capture errors, warnings, and logs in real-time

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See It In Action

Claude Desktop using VUDA to check links and find broken pages

Validating user registration flow with step-by-step screenshots

Taking screenshots via Puppeteer MCP integration

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Architecture

VUDA acts as a bridge between AI models and web browsers through the MCP protocol. It uses Playwright for reliable cross-browser automation and provides structured data that any AI can understand.

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Automated Testing Workflow

One command triggers a comprehensive site analysis - crawl all pages, screenshot everything, validate user flows, and measure performance in seconds.

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Quick Start

Installation

# Install globally via npm
npm install -g visual-ui-debug-agent-mcp

# Or run directly with npx (no installation needed)
npx visual-ui-debug-agent-mcp

Configure with Claude Desktop

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

{
  "mcpServers": {
    "vuda": {
      "command": "npx",
      "args": ["-y", "visual-ui-debug-agent-mcp"]
    }
  }
}

Configure with Other MCP Clients

{
  "mcpServers": {
    "vuda": {
      "command": "node",
      "args": ["/path/to/visual-ui-debug-agent-mcp/dist/index.js"]
    }
  }
}

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Complete Tool Reference (30 Tools)

Visual Analysis Tools

Tool	Description
enhanced_page_analyzer	Comprehensive page analysis with element mapping, performance metrics, and console logs
screenshot_url	Capture high-quality screenshots of any URL with device emulation
batch_screenshot_urls	Screenshot multiple URLs in a single operation
screenshot_local_files	Capture screenshots of local HTML files
visual_comparison	Compare two pages/states and highlight visual differences
dom_inspector	Inspect DOM elements with computed styles and properties

Workflow & Testing Tools

Tool	Description
ui_workflow_validator	Test complete user journeys with step-by-step validation
navigation_flow_validator	Validate multi-step navigation sequences
api_endpoint_tester	Test API endpoints with authentication support

Performance & Monitoring Tools

Tool	Description
performance_analysis	Measure page load performance and Core Web Vitals
console_monitor	Monitor and capture console logs, errors, and warnings
sitemap_crawler	Crawl sitemaps and analyze page structure

Playwright Direct Controls

Tool	Description
playwright_navigate	Navigate to URLs
playwright_click	Click on elements
playwright_iframe_click	Click elements inside iframes
playwright_fill	Fill form fields
playwright_select	Select dropdown options
playwright_hover	Hover over elements
playwright_evaluate	Execute JavaScript in page context
playwright_console_logs	Get console output
playwright_get_visible_text	Extract visible text content
playwright_get_visible_html	Get rendered HTML
playwright_go_back	Navigate back
playwright_go_forward	Navigate forward
playwright_press_key	Press keyboard keys
playwright_drag	Drag and drop elements
playwright_screenshot	Take custom screenshots

Utility Tools

Tool	Description
tunnel_helper	Guide and manage Cloudflare tunnel setup for remote debugging
debug_memory	Save and retrieve debugging context across sessions

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Usage Examples

Take a Screenshot

Ask Claude: "Take a screenshot of https://example.com"

The AI will use screenshot_url to capture the page and return the image.

Analyze a Page

Ask Claude: "Analyze the UI of https://myapp.com/dashboard and find any issues"

VUDA will use enhanced_page_analyzer to map all elements, check console for errors, and report findings.

Test a Login Flow

Ask Claude: "Test the login flow on https://myapp.com - use test@example.com and password123"

The AI will use ui_workflow_validator to:

1. Navigate to the login page
2. Fill in credentials
3. Click submit
4. Verify successful login
5. Capture screenshots at each step

Compare Two Versions

Ask Claude: "Compare the homepage before and after our CSS update"

Using visual_comparison, VUDA will highlight all visual differences between the two states.

Monitor Performance

Ask Claude: "Check the performance of our checkout page"

performance_analysis will measure load times, analyze Core Web Vitals, and identify bottlenecks.

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Advanced Configuration

Environment Variables

# Set browser options
PLAYWRIGHT_HEADLESS=true
PLAYWRIGHT_SLOW_MO=100

# Debug mode
DEBUG=vuda:*

Programmatic Usage

import { Server } from "@modelcontextprotocol/sdk/server/index.js";

// VUDA exposes all tools through the MCP protocol
const result = await client.callTool("enhanced_page_analyzer", {
  url: "https://example.com",
  includeConsole: true,
  mapElements: true,
  fullPage: true
});

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Why VUDA?

Feature	VUDA	Other Solutions
MCP Native	Built for AI integration	Often REST-only
30 Specialized Tools	Comprehensive coverage	Limited toolsets
Vision for Any AI	Works without built-in vision	Requires vision models
Autonomous Testing	AI-driven workflows	Manual scripting
Cross-Browser	Playwright-powered	Single browser
Zero Config	Works out of the box	Complex setup

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Requirements

• Node.js 18 or higher
• npm or npx
• Works on macOS, Linux, and Windows

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Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your 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

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License

This project is licensed under the ISC License.

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_{Built with Playwright and the Model Context Protocol
Made by @samihalawa}