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debugg-ai-mcp

@debugg-ai/debugg-ai-mcp
0 Stars 171 次浏览 debugg-ai 更新于 2026-08-23

MCP 服务配置

复制以下 JSON 到 OPClaw 或其他 MCP 客户端的配置文件中即可使用

{
  "mcpServers": {
    "debugg-ai-mcp": {
      "args": [
        "-y",
        "@debugg-ai/debugg-ai-mcp"
      ],
      "command": "npx",
      "env": {
        "DEBUGGAI_API_KEY": "your_api_key_here"
      }
    }
  }
}

服务介绍

Official MCP Server for Debugg AI

AI-powered development and testing toolkit implementing the Model Context Protocol (MCP), designed to give AI agents comprehensive testing, debugging, and code analysis capabilities.

Transform your development workflow with:

  • Zero-config E2E testing - Run browser tests with natural language descriptions
  • Live session monitoring - Real-time browser console, network, and screenshot monitoring
  • Test suite management - Create and manage comprehensive test suites
  • Seamless CI/CD integration - View all test results in your Debugg.AI App dashboard

Features

12 Focused Development Tools

  • E2E Testing Suite - Run browser tests, create test suites, and generate commit-based tests
  • Live Session Monitoring - Real-time browser console, network traffic, and screenshot monitoring
  • Test Management - List, create, and track test suites and commit-based test suites
  • Real-time Progress - Live updates with screenshots and step-by-step execution
  • Universal Compatibility - Works with any MCP-compatible client (Claude Desktop, LangChain, etc.)

Examples

Input prompt: "Test the ability to create an account and login"

Test Create Account and Login

Results:

**Task Completed**

- Duration: 86.80 seconds
- Final Result: Successfully completed the task of signing up and logging into the account with the email 'alice.wonderland1234@example.com'.
- Status: Success

Full Demo:

Watch a more in-depth, Full Use Case Demo


Quick Setup

1. Get Your API Key

Create a free account at debugg.ai and generate your API key.

2. Choose Your Installation Method

Option A: NPX (Recommended)

npx -y @debugg-ai/debugg-ai-mcp

Option B: Docker

docker run -i --rm --init \
  -e DEBUGGAI_API_KEY=your_api_key \
  quinnosha/debugg-ai-mcp

Available Tools

E2E Testing Tools

  • debugg_ai_test_page_changes - Run browser tests with natural language descriptions
  • debugg_ai_create_test_suite - Create organized test suites for features
  • debugg_ai_create_commit_suite - Generate tests based on git commits
  • debugg_ai_get_test_status - Monitor test execution and results

Test Management Tools

  • debugg_ai_list_tests - List all E2E tests with filtering and pagination
  • debugg_ai_list_test_suites - List all test suites with filtering options
  • debugg_ai_list_commit_suites - List all commit-based test suites

Live Session Monitoring Tools

  • debugg_ai_start_live_session - Start a live browser session with real-time monitoring
  • debugg_ai_stop_live_session - Stop an active live session
  • debugg_ai_get_live_session_status - Get the current status of a live session
  • debugg_ai_get_live_session_logs - Retrieve console and network logs from a live session
  • debugg_ai_get_live_session_screenshot - Capture screenshots from an active live session

Configuration

For Claude Desktop

Add this to your MCP settings file:

{
  "mcpServers": {
    "debugg-ai-mcp": {
      "command": "npx",
      "args": ["-y", "@debugg-ai/debugg-ai-mcp"],
      "env": {
        "DEBUGGAI_API_KEY": "your_api_key_here"
      }
    }
  }
}

Optional Environment Variables

# Required
DEBUGGAI_API_KEY=your_api_key

# Optional (with sensible defaults)
DEBUGGAI_LOCAL_PORT=3000                    # Your app's port
DEBUGGAI_LOCAL_REPO_NAME=your-org/repo      # GitHub repo name
DEBUGGAI_LOCAL_REPO_PATH=/path/to/project   # Project directory

Usage Examples

Run a Quick E2E Test

"Test the user login flow on my app running on port 3000"

Analyze Your Project

"What frameworks and languages are used in my codebase?"

Get Issue Insights

"Show me all high-priority issues in my project"

Generate Test Coverage

"Generate test coverage for the authentication module"

Local Development

# Install dependencies
npm install

# Run tests
npm test

# Build project
npm run build

# Start server locally
node dist/index.js

Project Structure

debugg-ai-mcp/
 config/          # Configuration management  
 tools/           # 14 MCP tool definitions
 handlers/        # Tool implementation logic
 services/        # DebuggAI API integration
 utils/           # Shared utilities & logging
 types/           # TypeScript type definitions
 __tests__/       # Comprehensive test suite
 index.ts         # Main server entry point

Publishing & Releases

This project uses automated publishing to NPM. Here's how it works:

Automatic Publishing

  • Every push to main triggers automatic NPM publishing
  • Only publishes if the version doesn't already exist
  • Includes full test suite validation and build verification

Version Management

# Bump version locally
npm run version:patch  # 1.0.15  1.0.16
npm run version:minor  # 1.0.15  1.1.0
npm run version:major  # 1.0.15  2.0.0

# Check package contents
npm run publish:check

Manual Version Bump via GitHub

  1. Go to Actions Version Bump
  2. Click "Run workflow"
  3. Select version type or enter custom version
  4. Workflow will update version and trigger publish

Setup for Contributors

See .github/PUBLISHING_SETUP.md for complete setup instructions.



License

Apache-2.0 License 2025 DebuggAI


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