Collection of Playwright MCP prompt files for automated and manual testing

MCP server providing Playwright test generation wizard with intelligent prompts and best practices

AI reads context and makes decisions for form filling (not just prompt calls) via Azure OpenAI. Uses Playwright MCP for browser control and web automation. Has strong error handling with retry/snapshot recovery. Supports human-in-the-loop flow via “Interactive Review: Optional confirmation before each submission.”

Submit natural language prompts to an AI chatbot, which will use a browser through an MCP (Model Context Protocol) server to perform actions and generate Playwright tests automatically.

This is an AI-driven test automation framework using natural language prompts with Playwright MCP

POCs y ejercicios de Strapi, n8n, Playwright, MCP, prompts y TypeScript para práctica Hazlo Ágil.

This repo demonstrates how to set up and use the **Playwright MCP Agent** with **GitHub Copilot** to build intelligent, prompt-driven test automation.

An interactive HTML graph built with Plotly.js to visualise New Zealand Government Debt Trends from 2002–2025 • The project include CICD Playwright automated end-to-end testing to verify page and graph features • Playwright MCP was used with GitHub Copilot, Claude Sonnet and Chat-GPT agent prompts to generate and fix automated tests.

Research project exploring Claude-based MCP integration with Playwright using TypeScript. Focused on evaluating AI-assisted E2E test generation, prompt structure, and real-time test scripting via Claude and VS Code Copilot.

Explore the playwright script generation and copilot prompt practice

Este repositorio contiene un ecosistema completo para la creación, configuración y generación automatizada de proyectos de testing con **Playwright BDD**. Es un metaproyecto que proporciona herramientas para scaffolding, instrucciones de desarrollo y prompts de generación de pruebas.

Playwright automation with MCP & Prompts in the CICD

SauceDemo framework created entirely using Playwright MCP Agents. No code, 100% prompts

Test generation prompt to use with the Playwright MCP server.

Scrappy, instant AI scraping CLI—prompt-driven extraction with Playwright MCP / Cheerio; Raspberry Pi-friendly.

Making a tiny project and checking whether just my giving prompts in copilot and using playwright MCP can we generate a test scrips !

Playwright-MCP combines Playwright's automation capabilities with AI-powered test generation through the Model Context Protocol. This integration allows you to generate intelligent test scripts using AI prompts and execute them with Playwright's robust testing framework.

Autonomous test automation framework using Playwright and Model Context Protocol (MCP). Supports natural language prompts for web exploration, UI interaction and adaptive test execution.

This repository demonstrates a prompt-driven test automation framework built using Playwright, MCP (Model Context Protocol), and GitHub Copilot.

AI-powered Playwright test generation framework for GitHub Copilot. Uses Playwright CLI + MCP servers + agent skills to explore web apps, create test plans, generate working .spec.ts files, and self-heal failing tests. All from natural language prompts.

Full project created with AI in VS code insider in playwright just added multiple MCP's and everything created on basis of prompting

# Integrate MCP with Copilot This repository demonstrates how to connect GitHub Copilot Agent Mode with Model Context Protocol (MCP) servers like GitHub, Figma, and Playwright. It provides setup notes, sample prompts, and workflows to practice agentic loops for research, planning, implementation, testing, and updates.

Projeto MCP (Model Context Protocol) para automação e testes E2E com Playwright. Suporta geração de testes via prompt, execução em Chromium, relatórios HTML e integração com TypeScript e Python.

This Playwright Model Context Protocol (MCP) project delivers robust automation for Dynamics 365 app. The framework combines traditional page objects with AI prompt-based testing approaches, allowing both technical and non-technical users to create and maintain tests. By leveraging storage state authentication and comprehensive error handling.