AI QA Agent MCP

AI QA Agent MCP

Analyzes Playwright test results to provide structured QA insights, including test metrics, failure analysis, bug report drafts, and release-quality recommendations.

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README

AI QA Agent MCP

A TypeScript-based Model Context Protocol server that analyzes Playwright test results and provides structured QA insights.

Project Goal

This project demonstrates how an AI agent can use MCP tools to:

  • Discover Playwright test-result files
  • Calculate test execution metrics
  • Analyze failed and flaky tests
  • Group similar failures
  • Generate QA execution summaries
  • Create draft bug reports
  • Provide release-quality recommendations

Planned MCP Capabilities

Tools

  • list_test_runs
  • get_test_run_summary
  • analyze_test_failures
  • generate_bug_report
  • generate_qa_summary

Resource

  • test-run://latest

Prompt

  • prepare-release-quality-report

Technology Stack

  • Node.js
  • TypeScript
  • Model Context Protocol TypeScript SDK
  • Zod
  • Vitest
  • Playwright JSON and JUnit reports
  • GitHub Actions
  • MCP Inspector
  • Codex CLI

Planned Architecture

Playwright Test Results
          |
          v
Report Parsers
          |
          v
QA Analysis Services
          |
          v
MCP Server
    |       |       |
  Tools  Resources  Prompts
          |
          v
MCP Inspector or AI Client

Project Structure

ai-qa-agent-mcp/
├── .github/
│   └── workflows/
├── docs/
├── reports/
├── sample-data/
│   ├── json/
│   └── junit/
├── src/
│   ├── config/
│   ├── parsers/
│   ├── prompts/
│   ├── resources/
│   ├── schemas/
│   ├── services/
│   ├── tools/
│   ├── types/
│   └── server.ts
├── tests/
│   ├── integration/
│   └── unit/
├── .gitignore
├── package.json
├── README.md
└── tsconfig.json

Development Commands

Install dependencies:

npm install

Run the server during development:

npm run dev

Check TypeScript:

npm run typecheck

Run automated tests:

npm test

Build the project:

npm run build

Run all validations:

npm run check

Security Principles

  • Read-only report access by default
  • Restricted file-system access
  • Input validation for every MCP tool
  • No automatic issue creation
  • No secret values in logs
  • Human review required for AI-generated conclusions

Current Status

Version 0.1.0 is under development.

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