Debugg.ai Mcp: Zero Config, Ai Managed End To End Tests

创建者

debugg-aia year ago

🧪 Official MCP Server for Debugg AI AI-driven browser automation and E2E test server implementing the Model Context Protocol (MCP), designed to help AI agents test UI changes, simulate user behavior, and analyze visual outputs of running web applications — all via natural language and CLI tools.

# browser automation

# code testing

概览内容工具评论

概览

🛠️ Quickstart

Ensure you have created a free account and generated an API Key - DebuggAI

Option 1: NPX (Local Development)

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

Use this when testing or integrating into tools like Claude Desktop or your own AI agent.

Option 2: Docker

docker run -i --rm --init \
  -e DEBUGGAI_API_KEY=your_api_key \
  -e TEST_USERNAME_EMAIL=your_test_email \
  -e TEST_USER_PASSWORD=your_password \
  -e DEBUGGAI_LOCAL_PORT=3000 \
  -e DEBUGGAI_LOCAL_REPO_NAME=your-org/your-repo \
  -e DEBUGGAI_LOCAL_BRANCH_NAME=main \
  -e DEBUGGAI_LOCAL_REPO_PATH=/app \
  -e DEBUGGAI_LOCAL_FILE_PATH=/app/index.ts \
  quinnosha/debugg-ai-mcp

🧰 MCP Tool: `debugg_ai_test_page_changes`

Description

Run an end-to-end test on a running web app, testing a UI feature or flow described in natural language. Allows AI agents in ANY code gen platform to quickly evaluate proposed changes and ensure new functionality works as expected.

Input Parameters

Name	Type	Required	Description
`description`	string	✅	What feature or page to test (e.g. "Signup page form")
`localPort`	number	❌	Port of your running app (default: `3000`)
`repoName`	string	❌	GitHub repo name
`branchName`	string	❌	Current branch
`repoPath`	string	❌	Absolute path to the repo
`filePath`	string	❌	File to test

🧪 Example Claude Desktop Config

{
  "mcpServers": {
    "debugg-ai-mcp": {
      "command": "npx",
      "args": ["-y", "@debugg-ai/debugg-ai-mcp"],
      "env": {
        "DEBUGGAI_API_KEY": "YOUR_API_KEY",
        "TEST_USERNAME_EMAIL": "test@example.com",
        "TEST_USER_PASSWORD": "supersecure",
        "MCP_REQUEST_TIMEOUT_RESET_ON_PROGRESS": "true",
        "DEBUGGAI_LOCAL_PORT": 3000,
        "DEBUGGAI_LOCAL_REPO_NAME": "org/project",
        "DEBUGGAI_LOCAL_BRANCH_NAME": "main",
        "DEBUGGAI_LOCAL_REPO_PATH": "/Users/you/project",
        "DEBUGGAI_LOCAL_FILE_PATH": "/Users/you/project/index.ts"
      }
    }
  }
}

🔐 Environment Variables

Variable	Description	Required
`DEBUGGAI_API_KEY`	API key for calling DebuggAI backend	✅
`TEST_USERNAME_EMAIL`	Email of test user account	❌
`TEST_USER_PASSWORD`	Password of test user account	❌
`DEBUGGAI_LOCAL_PORT`	Local port your app runs on	✅
`DEBUGGAI_LOCAL_REPO_NAME`	GitHub repo name	❌
`DEBUGGAI_LOCAL_BRANCH_NAME`	Branch name	❌
`DEBUGGAI_LOCAL_REPO_PATH`	Local path to repo root	❌
`DEBUGGAI_LOCAL_FILE_PATH`	File to test	❌
`MCP_REQUEST_TIMEOUT_RESET_ON_PROGRESS`	Prevents client timeouts during long tests	❌

🧑‍💻 Local Development

# Clone the repo and install dependencies
npm install

# Copy the test config and insert your creds
cp test-config-example.json test-config.json

# Run the MCP server locally
npx @modelcontextprotocol/inspector --config debugg-ai-mcp/test-config.json --server debugg-ai-mcp

📁 Repo Structure

.
├── e2e-agents/             # E2E browser test runners
├── services/               # Client for DebuggAI API
├── tunnels /               # Secure connections to remote web browsers
├── index.ts                # Main MCP server entry
├── Dockerfile              # Docker build config
└── README.md

🧱 Built With

Model Context Protocol SDK

💬 Feedback & Issues

For bugs, ideas, or integration help, open an issue or contact the DebuggAI team directly.

🔒 License

Made with 🩸, 💦, and 😭 in San Francisco

服务器配置

{
  "mcpServers": {
    "debugg-ai-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "@debugg-ai/debugg-ai-mcp"
      ],
      "env": {
        "DEBUGGAI_API_KEY": "your key here",
        "TEST_USERNAME_EMAIL": "test email here",
        "TEST_USER_PASSWORD": "test password here",
        "DEBUGGAI_LOCAL_PORT": 3000
      }
    },
    "debugg-ai-mcp-docker": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "--init",
        "-e",
        "DEBUGGAI_API_KEY=your key here",
        "-e",
        "DEBUGGAI_LOCAL_PORT=3000",
        "quinnosha/debugg-ai-mcp"
      ],
      "env": {
        "DEBUGGAI_API_KEY": "your key here",
        "DEBUGGAI_LOCAL_PORT": 3000
      }
    }
  }
}

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