DebuggAI▌
by debugg-ai
DebuggAI enables zero-config end to end testing for web applications, offering secure tunnels, easy setup, and detailed
Provides zero-configuration end-to-end testing for web applications by creating secure tunnels to local development servers and spawning testing agents that interact with web interfaces through natural language descriptions, returning detailed test results with execution recordings and screenshots.
Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.
best for
- / Frontend developers testing local development builds
- / QA teams automating browser-based test scenarios
- / CI/CD pipelines requiring end-to-end validation
- / Teams needing quick smoke tests of web applications
capabilities
- / Test web applications using natural language descriptions
- / Create secure tunnels to local development servers
- / Generate screenshots and execution recordings of tests
- / Handle user authentication with stored credentials
- / Navigate and interact with web interfaces automatically
- / Return detailed pass/fail test results
what it does
Runs AI-powered browser testing agents that navigate your web app using natural language test descriptions and return pass/fail results with screenshots. Creates secure tunnels to test local development servers without manual setup.
about
DebuggAI is a community-built MCP server published by debugg-ai that provides AI assistants with tools and capabilities via the Model Context Protocol. DebuggAI enables zero-config end to end testing for web applications, offering secure tunnels, easy setup, and detailed It is categorized under browser automation, developer tools.
how to install
You can install DebuggAI in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
license
Apache-2.0
DebuggAI is released under the Apache-2.0 license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
readme
Debugg AI — MCP Server
AI-powered browser testing via the Model Context Protocol. Point it at any URL (or localhost) and describe what to test — an AI agent browses your app and returns pass/fail with screenshots.
<a href="https://glama.ai/mcp/servers/@debugg-ai/debugg-ai-mcp"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@debugg-ai/debugg-ai-mcp/badge" alt="Debugg AI MCP server" /> </a>Setup
Get an API key at debugg.ai, then add to your MCP client config:
{
"mcpServers": {
"debugg-ai": {
"command": "npx",
"args": ["-y", "@debugg-ai/debugg-ai-mcp"],
"env": {
"DEBUGGAI_API_KEY": "your_api_key_here"
}
}
}
}
Or with Docker:
docker run -i --rm --init -e DEBUGGAI_API_KEY=your_api_key quinnosha/debugg-ai-mcp
check_app_in_browser
Runs an AI browser agent against your app. The agent navigates, interacts, and reports back with screenshots.
| Parameter | Type | Description |
|---|---|---|
description | string required | What to test (natural language) |
url | string | Target URL — required if localPort not set |
localPort | number | Local dev server port — tunnel created automatically |
environmentId | string | UUID of a specific environment |
credentialId | string | UUID of a specific credential |
credentialRole | string | Pick a credential by role (e.g. admin, guest) |
username | string | Username for login |
password | string | Password for login |
Configuration
DEBUGGAI_API_KEY=your_api_key
Local Development
npm install && npm test && npm run build
Links
Dashboard · Docs · Issues · Discord
Apache-2.0 License © 2025 DebuggAI
FAQ
- What is the DebuggAI MCP server?
- DebuggAI is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
- How do MCP servers relate to agent skills?
- Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
- How are reviews shown for DebuggAI?
- This profile displays 38 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.5 out of 5—verify behavior in your own environment before production use.
Use Cases▌
Web Research & Information Gathering
Fetch and extract information from websites automatically
Example
Research competitor pricing, scrape product reviews, monitor news mentions
Automate 5-10 hours/week of manual web research
Content Monitoring & Alerts
Track website changes, new content, price updates
Example
Monitor competitor blog for new posts, track stock availability, watch for pricing changes
Stay informed without manual checking, never miss important updates
Data Extraction & Aggregation
Extract structured data from multiple websites
Example
Compile product listings from 10 e-commerce sites, aggregate job postings, collect real estate data
Build datasets 100x faster than manual copying
API-less Integration
Interact with services that don't offer APIs
Example
Check form submissions, validate website functionality, test user flows
Automate interactions with any website, even without API
Implementation Guide▌
Prerequisites
- ›Claude Desktop or Cursor with MCP support
- ›Understanding of web scraping ethics and robots.txt
- ›Rate limiting awareness to avoid overwhelming target sites
- ›Knowledge of legal restrictions on data collection
Time Estimate
20-40 minutes including configuration and testing
Installation Steps
- 1.Install web automation MCP server via npm or pip
- 2.Configure allowed domains and rate limits in MCP config
- 3.Test with simple fetch: 'Get content from example.com'
- 4.Progress to extraction: 'Extract all product prices from this page'
- 5.Set up monitoring: 'Check this URL daily for changes'
- 6.Parse structured data: 'Create CSV from this table'
- 7.Respect robots.txt and rate limits always
Troubleshooting
- ⚠403 Forbidden: Website blocks bots—respect their wishes, use official API instead
- ⚠Rate limit errors: Slow down requests, add delays between fetches
- ⚠Stale data: Target site changed HTML structure—update selectors
- ⚠Timeout errors: Site is slow or blocking—increase timeout, try different user agent
- ⚠JavaScript-rendered content: Use headless browser MCP servers for dynamic sites
Best Practices▌
✓ Do
- +Check robots.txt and respect crawl rules
- +Rate limit requests: 1-2 requests/second maximum
- +Use official APIs when available instead of scraping
- +Identify your bot with descriptive user agent
- +Cache results to minimize repeated requests
- +Handle errors gracefully with retries and fallbacks
- +Validate extracted data for accuracy
✗ Don't
- −Don't scrape sites that explicitly forbid it (robots.txt, ToS)
- −Don't overwhelm servers with rapid requests—use rate limiting
- −Don't scrape personal data without consent and legal basis
- −Don't ignore copyright on extracted content
- −Don't assume HTML structure is stable—handle changes
- −Don't use scraped data for commercial purposes without permission
💡 Pro Tips
- ★Use CSS selectors or XPath for robust data extraction
- ★Set up monitoring alerts for extraction failures (structure changed)
- ★Implement exponential backoff for retries on failures
- ★Store raw HTML for reprocessing if extraction logic changes
- ★Combine with data analysis tools for insights from extracted data
- ★Consider using official APIs or RSS feeds as more stable alternatives
Technical Details▌
Architecture
MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.
Protocols
- HTTP/HTTPS
- WebSocket (for real-time sites)
- Puppeteer/Playwright (for JavaScript sites)
Compatibility
- Static HTML sites
- JavaScript-rendered SPAs (with headless browser)
- REST APIs
- GraphQL endpoints
When to Use This▌
✓ Use When
Use for research automation, content monitoring, data aggregation from multiple sources, and when official APIs don't exist. Best for read-only information gathering.
✗ Avoid When
Avoid for sites with APIs (use API instead), sites that explicitly forbid scraping, when data is copyrighted, or for login-required content without proper authorization.
Integration▌
- →Scheduled monitoring with change detection
- →Multi-source data aggregation pipelines
- →Fallback to web scraping when API rate limits hit
- →Headless browser for JavaScript-heavy sites
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
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Ratings
4.5★★★★★38 reviews- ★★★★★Pratham Ware· Dec 28, 2024
Useful MCP listing: DebuggAI is the kind of server we cite when onboarding engineers to host + tool permissions.
- ★★★★★Dhruvi Jain· Dec 24, 2024
We wired DebuggAI into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Charlotte Kapoor· Dec 4, 2024
Strong directory entry: DebuggAI surfaces stars and publisher context so we could sanity-check maintenance before adopting.
- ★★★★★Maya Singh· Dec 4, 2024
DebuggAI is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
- ★★★★★Henry Ramirez· Nov 23, 2024
I recommend DebuggAI for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
- ★★★★★Charlotte Lopez· Nov 23, 2024
According to our notes, DebuggAI benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
- ★★★★★Oshnikdeep· Nov 15, 2024
DebuggAI is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
- ★★★★★Xiao Mensah· Oct 14, 2024
DebuggAI reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
- ★★★★★Arya Patel· Oct 14, 2024
We wired DebuggAI into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
- ★★★★★Ganesh Mohane· Oct 6, 2024
DebuggAI is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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