MCP server
by debugg-ai
DebuggAI enables zero-config end to end testing for web applications, offering secure tunnels, easy setup, and detailed
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.
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.
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.
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.
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
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
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
Share your MCP server with the developer community
Useful MCP listing: DebuggAI is the kind of server we cite when onboarding engineers to host + tool permissions.
We wired DebuggAI into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Strong directory entry: DebuggAI surfaces stars and publisher context so we could sanity-check maintenance before adopting.
DebuggAI is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
I recommend DebuggAI for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
According to our notes, DebuggAI benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
DebuggAI is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
DebuggAI reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
We wired DebuggAI into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
DebuggAI is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
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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>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_browserRuns 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 |
DEBUGGAI_API_KEY=your_api_key
npm install && npm test && npm run build
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Apache-2.0 License © 2025 DebuggAI
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
Prerequisites
Time Estimate
20-40 minutes including configuration and testing
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.
Protocols
Compatibility
✓ 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.