QA Copilot AI
БесплатноНе проверенMCP server for AI-powered QA analysis. It enables analyzing test failures, identifying root causes, suggesting fixes, classifying defects, detecting flaky tests
Описание
MCP server for AI-powered QA analysis. It enables analyzing test failures, identifying root causes, suggesting fixes, classifying defects, detecting flaky tests, and generating test cases and bug reports.
README

An AI-powered QA Assistant that helps QA engineers analyze test failures, identify root causes, generate fixes, classify defects, detect flaky tests, and automate testing activities using MCP, TypeScript, and Large Language Models.
🚀 Project Overview
Modern QA teams spend significant time analyzing failed automation tests, debugging errors, writing bug reports, and identifying flaky tests.
QA Copilot AI is an AI-assisted testing platform designed to reduce debugging effort by combining:
- Model Context Protocol (MCP)
- Large Language Models (Groq LLM)
- Playwright automation data
- REST APIs
- TypeScript backend services
The system allows QA engineers to provide test reports and receive AI-generated insights such as:
- Root cause analysis
- Failure classification
- Suggested fixes
- Test improvement recommendations
- Automated QA artifacts
🎯 Problem Statement
Automation failures often require manual investigation:
❌ Reading long stack traces ❌ Finding root causes ❌ Identifying flaky tests ❌ Writing defect reports ❌ Creating repetitive test cases
QA Copilot AI solves this by acting as an intelligent testing assistant.
✨ Features
AI-Powered QA Analysis
✅ Failure Analysis ✅ Test Report Analysis ✅ Root Cause Identification ✅ Fix Suggestions ✅ Failure Classification ✅ Flaky Test Detection
Test Automation Assistance
✅ API Test Generator ✅ Test Case Generator ✅ Playwright Script Generator ✅ Bug Report Generator
Engineering Features
✅ MCP Server Implementation ✅ REST API using Express.js ✅ Modular TypeScript Architecture ✅ Environment Configuration ✅ Error Handling ✅ Logging Utilities
🏗 System Architecture

Workflow:
QA Engineer
|
|
Test Reports / Logs
|
v
QA Copilot API
|
v
MCP Server
|
|
-----------------------------
| | | |
Failure Report Fix Flaky
Analyzer Analyzer Suggest Detector
|
v
Groq Large Language Model
|
v
AI Generated QA Insights
🛠 Tech Stack
| Category | Technology |
|---|---|
| Language | TypeScript |
| Runtime | Node.js |
| Backend | Express.js |
| AI Model | Groq LLM |
| Protocol | Model Context Protocol |
| Automation | Playwright |
| Package Manager | npm |
| Configuration | dotenv |
📁 Project Structure
QA-Copilot-AI
src/
├── ai/
│ └── promptTemplates.ts
|
├── api/
|
├── mcp-server/
|
├── tools/
|
├── services/
|
├── config/
|
└── utils/
docs/
├── architecture.png
└── architecture.md
screenshots/
package.json
README.md
⚙ Installation
Clone repository:
git clone https://github.com/Sham-coder16/qa-copilot-ai.git
Navigate:
cd qa-copilot-ai
Install dependencies:
npm install
🔑 Environment Setup
Create .env
GROQ_API_KEY=your_api_key
PORT=3000
▶ Running Application
Start MCP Server
npm run mcp
Expected:
MCP SERVER STARTED
Tools Registered Successfully
Start API Server
npm run api
Expected:
API Server running on port 3000
Run Test Client
npx tsx src/test-client.ts
🔧 MCP Tools
Available tools:
| Tool | Purpose |
|---|---|
| Failure Analyzer | Analyze failed tests |
| Report Analyzer | Analyze execution reports |
| Suggest Fix | Generate solutions |
| Failure Classification | Categorize failures |
| Flaky Detector | Detect unstable tests |
| Test Generator | Generate automation tests |
| Bug Generator | Create defect reports |
📡 REST API Example
Endpoint:
POST /analyze
Request:
{
"failure": "Login test failed due to timeout"
}
Response:
{
"category":"Automation Failure",
"rootCause":"Element loading issue",
"suggestion":"Increase explicit wait"
}
📸 Screenshots
📸 Project Screenshots
MCP Server Running

API Server Running

AI Failure Analysis

Bug Report Generation

Test Case Generation

🔄 Future Enhancements
- Docker Support
- GitHub Actions CI/CD
- Jenkins Pipeline Integration
- Database Storage
- Web Dashboard
- Multiple LLM Provider Support
- Playwright HTML Report Integration
💡 Skills Demonstrated
- QA Automation
- Playwright Testing
- TypeScript Development
- Node.js Backend
- REST API Development
- AI Integration
- Prompt Engineering
- MCP Architecture
- LLM Testing Concepts
- GitHub Project Management
👩💻 Author
Shamli Kadukar
GitHub:
https://github.com/Sham-coder16
⭐ If this project helped you understand AI-powered QA automation, consider starring the repository.
Установка QA Copilot AI
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/Sham-coder16/qa-copilot-aiFAQ
QA Copilot AI MCP бесплатный?
Да, QA Copilot AI MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для QA Copilot AI?
Нет, QA Copilot AI работает без API-ключей и переменных окружения.
QA Copilot AI — hosted или self-hosted?
Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.
Как установить QA Copilot AI в Claude Desktop, Claude Code или Cursor?
Открой QA Copilot AI на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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