Playwright Python AI Framework MCP sunucusu

🤖 AI-Powered Test Automation Framework

Playwright • Python • MCP • GitHub Copilot • API Testing • Page Object Model

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🚀 Overview

Artificial Intelligence is rapidly transforming Software Quality Engineering.

Modern QA Engineers are expected to build scalable automation frameworks while leveraging AI to accelerate software delivery.

This repository demonstrates how Playwright, Python, GitHub Copilot, and Model Context Protocol (MCP) can work together to build modern, AI-assisted automation solutions.

Instead of treating AI as an autocomplete tool, this project explores how AI can become a productivity partner throughout the testing lifecycle—from framework development to UI automation, API validation, and test generation.

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🎯 Project Goals

This repository demonstrates practical implementation of:

• AI-Assisted Test Development
• UI Automation with Playwright
• API Automation
• Page Object Model (POM)
• Python Automation Framework Design
• MCP (Model Context Protocol) Concepts
• GitHub Copilot Assisted Development
• Modern Test Automation Practices

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🏗 Framework Architecture

ai_playwright_python_using_mcpandgithubcopilot
│
├── AITesting
│   ├── Test_CodeCompletion.py
│   ├── search_product.py
│
├── ai
│   ├── pages
│   │
│   ├── test_apitest_mcp.py
│   ├── test_login_logout.py
│
├── requirements.txt
│
└── README.md

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✨ Key Features

🤖 AI-Assisted Automation

This project demonstrates how GitHub Copilot can improve productivity by assisting with:

• Test generation
• Assertion creation
• Locator suggestions
• Refactoring
• Boilerplate reduction
• Framework development

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🎭 UI Automation

Implemented using Playwright.

Covered scenarios include:

• Login
• Logout
• Search
• Navigation
• End-to-End User Flow
• Browser Automation

Benefits

• Auto Waits
• Cross Browser Testing
• Fast Execution
• Reliable Locators

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🌐 API Testing

The framework demonstrates:

• GET Requests
• POST Requests
• API Validation
• Status Code Validation
• Response Validation
• Business Rule Verification

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🔗 MCP (Model Context Protocol)

This repository explores early adoption of MCP concepts for software testing.

Areas explored include:

• Context-aware automation
• AI tool integration
• Smarter developer workflows
• Future-ready automation engineering

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📦 Page Object Model

Framework follows Page Object Model principles.

Advantages

• Better maintainability
• Reusable components
• Scalable architecture
• Cleaner test scripts

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💻 Technology Stack

Technology	Purpose
Python	Programming Language
Playwright	UI Automation
Pytest	Test Execution
GitHub Copilot	AI Assisted Development
MCP	Context-Aware AI
Git	Version Control
GitHub	Source Control

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🧪 Test Scenarios

UI Testing

• Login
• Logout
• Search Products
• Navigation
• User Journey Validation

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API Testing

• Request Validation
• Response Validation
• Status Code Verification
• Backend Functional Testing

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AI-Assisted Development

• Test Creation
• Locator Suggestions
• Code Refactoring
• Productivity Enhancement

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🚀 Getting Started

Clone Repository

git clone https://github.com/ArpitChoubey/ai_playwright_python_using_mcpandgithubcopilot.git

Install dependencies

pip install -r requirements.txt

Install Playwright

playwright install

Run Tests

pytest

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📈 Skills Demonstrated

Automation

• Playwright
• Python
• API Testing
• UI Testing
• End-to-End Testing

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Framework Design

• Page Object Model
• Reusable Components
• Test Organization
• Scalable Architecture

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AI Engineering

• GitHub Copilot
• AI-Assisted Development
• MCP Concepts
• AI Productivity

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Software Engineering

• Python
• OOP
• Test Design
• Automation Strategy
• Maintainable Code

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💼 Why This Repository Matters

Traditional automation repositories often demonstrate:

• Login Tests
• CRUD Operations
• Basic Frameworks

This project goes beyond traditional automation by showcasing how modern AI tools can enhance software testing workflows.

It reflects an engineering mindset focused on:

• Continuous Learning
• Emerging Technologies
• Automation Innovation
• Developer Productivity
• Future-Ready Quality Engineering

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🚀 Future Roadmap

Planned enhancements include:

• Allure Reports
• GitHub Actions
• CI/CD Pipelines
• Docker Support
• Parallel Execution
• AI Generated Test Cases
• Self-Healing Automation
• Visual Testing
• Advanced MCP Integrations
• AI-Based Defect Analysis

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🎯 Ideal For

This repository is valuable for:

• QA Automation Engineers
• SDETs
• Software Test Engineers
• Python Developers
• Playwright Engineers
• AI Enthusiasts
• Hiring Managers evaluating automation portfolios

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👨‍💻 About Me

Arpit Choubey

SDET | QA Automation Engineer | Playwright | Selenium | REST Assured | Python | Java | API Testing | AI-Assisted Testing

I enjoy designing scalable automation frameworks, exploring AI-driven testing approaches, and sharing practical learning through open-source projects.

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🌐 Connect With Me

GitHub

https://github.com/ArpitChoubey

LinkedIn

https://www.linkedin.com/in/arpitchoubey/

Medium

https://medium.com/@ArpitChoubey9

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⭐ Support

If this repository helped you learn modern AI-assisted automation techniques, please consider giving it a Star ⭐.

Your support motivates me to continue building practical automation projects for the QA community.

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📌 Recruiter Snapshot

In less than 60 seconds, this repository demonstrates experience with:

✅ Playwright

✅ Python

✅ API Automation

✅ UI Automation

✅ Page Object Model

✅ AI-Assisted Development

✅ GitHub Copilot

✅ MCP Concepts

✅ Automation Framework Design

✅ Modern Software Testing Practices

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💡 Key Takeaway

"The future of software testing isn't AI replacing testers—it's testers who know how to leverage AI to deliver better software, faster."