Playwright Wizard MCP Server
Guides users through creating professional Playwright test suites with a step-by-step wizard workflow, including analysis, planning, setup, and implementation.
README
Playwright Wizard MCP Server
š§āāļø An intelligent Model Context Protocol (MCP) server that guides you through creating professional Playwright test suites with best practices built in.
Overview
Playwright Wizard MCP provides a structured, step-by-step approach to building comprehensive E2E test suites. Instead of starting from scratch or copying boilerplate, this MCP server guides you through industry best practices with intelligent prompts tailored to your application.
Features
- š§āāļø Step-by-step wizard workflow for creating comprehensive test suites
- š Comprehensive prompts covering analysis, planning, setup, and implementation
- šÆ Best practices for selectors, fixtures, and parallel execution
- š§ Optional enhancements for accessibility and API testing
- š Reference documentation for advanced patterns
- š MCP Registry integration for easy discovery and installation
Prerequisites
- Node.js 18 or higher
- An MCP-compatible client:
- GitHub Copilot in VS Code (with MCP support)
- Claude Desktop
- Cline (VS Code extension)
- Any other MCP-compatible AI client
Installation
Quick Start (Recommended)
No installation required! Use npx to run the server on-demand:
{
"mcpServers": {
"playwright-wizard": {
"command": "npx",
"args": ["-y", "playwright-wizard-mcp"]
}
}
}
This approach automatically uses the latest version without managing local installations.
Global Installation
For faster startup and offline use:
npm install -g playwright-wizard-mcp
Then configure without npx:
{
"mcpServers": {
"playwright-wizard": {
"command": "playwright-wizard-mcp"
}
}
}
From MCP Registry
Also available in the official MCP Registry for easy discovery.
Configuration
GitHub Copilot (VS Code)
-
Open your MCP config file:
- macOS:
~/Library/Application Support/Code/User/mcp.json - Windows:
%APPDATA%\Code\User\mcp.json
- macOS:
-
Add the server configuration:
{
"servers": {
"playwright-wizard": {
"command": "npx",
"args": ["-y", "playwright-wizard-mcp@latest"],
"type": "stdio"
}
}
}
- Restart VS Code or reload window (Cmd/Ctrl + Shift + P ā "Developer: Reload Window")
- Open GitHub Copilot Chat and verify tools are available
Claude Desktop
-
Open your config file:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
- macOS:
-
Add the server configuration:
{
"mcpServers": {
"playwright-wizard": {
"command": "npx",
"args": ["-y", "playwright-wizard-mcp"]
}
}
}
- Restart Claude Desktop
- Verify installation by seeing the šØ tool icon when you open a new chat
Cline (VS Code)
- Open VS Code
- Go to Cline settings (Cmd/Ctrl + Shift + P ā "Cline: Open MCP Settings")
- Add the server configuration:
{
"mcpServers": {
"playwright-wizard": {
"command": "npx",
"args": ["-y", "playwright-wizard-mcp"]
}
}
}
- Restart VS Code
- Look for Playwright Wizard tools in Cline's available tools list
Available Tools
Playwright Wizard exposes 15 tools organized into three categories: core workflow, optional enhancements, and reference documentation.
Core Workflow (Complete in Order)
These 5 tools guide you through creating a complete, production-ready test suite:
| Tool | Purpose | What It Creates | When to Use |
|---|---|---|---|
| analyze-app | Analyzes your application structure and tech stack | project-config.md, pages.md, selector-strategy.md |
Start here - First step for any new test suite |
| generate-test-plan | Creates comprehensive test scenarios and acceptance criteria | test-plan.md with suites, flows, and edge cases |
After analyzing the app |
| setup-infrastructure | Sets up Playwright config, fixtures, and folder structure | playwright.config.ts, fixtures, test helpers |
After test plan is ready |
| generate-page-objects | Generates type-safe page object models with optimal selectors | Page object files in tests/pages/ |
After infrastructure is set up |
| implement-test-suite | Writes actual tests with assertions and error handling | Complete test files in tests/ |
Final step - implement all planned tests |
Optional Enhancements
Add these capabilities after completing the core workflow:
| Tool | Purpose | What It Adds | When to Use |
|---|---|---|---|
| setup-ci-cd | Adds GitHub Actions for automated testing | .github/workflows/playwright.yml |
When you need CI/CD integration |
| add-accessibility | Integrates axe-core for WCAG 2.1 AA compliance | Accessibility test helpers and examples | For accessibility requirements |
| add-api-testing | Adds REST/GraphQL/tRPC API testing | API test utilities and examples | When testing backend APIs |
| advanced-optimization | Deep performance optimization and auth state reuse | Advanced patterns and configs | For complex apps with performance needs |
Reference Documentation
Access these anytime for additional context and patterns:
| Tool | Content | Use When |
|---|---|---|
| reference-core-principles | Core testing principles and quality standards | You need guidance on best practices |
| reference-workflow-overview | Complete workflow explanation and prompt relationships | You want to understand the big picture |
| reference-mcp-setup | MCP server setup and usage patterns | Having installation or configuration issues |
| reference-selector-strategies | Selector best practices and HTML quality scoring | Need help choosing the right selectors |
| reference-fixture-patterns | Playwright fixture patterns for parallel execution | Working with fixtures or state management |
| reference-data-storage-patterns | Test data storage patterns (ORM, JSON, MSW) | Need guidance on test data management |
How to Use the Tools
Simply ask your AI assistant to use them:
"Use the analyze-app tool to help me understand my application"
"Run the generate-test-plan tool to create test scenarios"
"Use setup-infrastructure to configure Playwright"
The AI will call the appropriate tool, receive detailed instructions, and execute them automatically. You'll see the results (files created, analysis completed) without seeing the internal instructions.
Getting Started
First-Time Setup (5 minutes)
- Install and configure the MCP server (see Configuration above)
- Restart your AI client (Claude Desktop or VS Code)
- Verify installation: Open a new chat and look for the šØ tool icon
Creating Your First Test Suite (30-60 minutes)
Here's what a typical workflow looks like:
Step 1: Analyze Your Application
You: "Help me analyze my React app for Playwright testing"
AI: *Calls analyze-app tool*
- Detects React, TypeScript, Vite from package.json
- Browses key pages (/, /login, /dashboard)
- Evaluates DOM quality and accessibility
- Creates .playwright-wizard-mcp/ folder with analysis files
AI: "ā
Analysis complete! Your app uses React + TypeScript with Vite.
I found 5 key pages. HTML quality is good (score: 8/10).
Created project-config.md, pages.md, and selector-strategy.md."
Step 2: Generate Test Plan
You: "Create a test plan based on the analysis"
AI: *Calls generate-test-plan tool*
- Creates comprehensive test scenarios
- Defines user flows and edge cases
- Specifies acceptance criteria
- Adds test data requirements
AI: "ā
Test plan created! I've defined 4 test suites:
- Authentication (5 scenarios)
- Dashboard (7 scenarios)
- User Profile (4 scenarios)
- Settings (3 scenarios)
See test-plan.md for details."
Step 3: Set Up Infrastructure
You: "Set up the Playwright infrastructure"
AI: *Calls setup-infrastructure tool*
- Creates playwright.config.ts with optimal settings
- Sets up fixtures for parallel execution
- Creates folder structure (tests/, pages/, fixtures/)
- Adds test helpers and utilities
AI: "ā
Infrastructure ready!
- Created playwright.config.ts (3 browsers, parallel mode)
- Set up custom fixtures for test isolation
- Organized folder structure
Ready for page objects!"
Step 4: Generate Page Objects
You: "Generate page object models"
AI: *Calls generate-page-objects tool*
- Creates type-safe page objects
- Uses optimal selectors (getByRole, getByLabel)
- Adds TypeScript types
- Implements reusable methods
AI: "ā
Page objects created!
- tests/pages/LoginPage.ts
- tests/pages/DashboardPage.ts
- tests/pages/ProfilePage.ts
All use accessible selectors and TypeScript."
Step 5: Implement Tests
You: "Implement the test suite"
AI: *Calls implement-test-suite tool*
- Writes complete test files
- Adds proper assertions and error handling
- Verifies parallel execution
- Optimizes performance
AI: "ā
Test suite complete!
- Created 19 tests across 4 suites
- All tests pass ā
- Average execution: 12s (parallel)
- 100% of tests use page objects
Run: npx playwright test"
What Gets Created
The wizard creates a complete test infrastructure in your project:
your-app/
āāā .playwright-wizard-mcp/ # Workflow documentation
ā āāā project-config.md # Tech stack analysis
ā āāā pages.md # Page inventory
ā āāā selector-strategy.md # Selector approach
ā āāā test-plan.md # Test scenarios
āāā tests/
ā āāā pages/ # Page object models
ā ā āāā LoginPage.ts
ā ā āāā DashboardPage.ts
ā ā āāā ProfilePage.ts
ā āāā fixtures/ # Custom fixtures
ā ā āāā authFixture.ts
ā āāā helpers/ # Test utilities
ā ā āāā testHelpers.ts
ā āāā auth.spec.ts # Test files
ā āāā dashboard.spec.ts
ā āāā profile.spec.ts
āāā playwright.config.ts # Playwright configuration
Next Steps
After completing the core workflow, consider:
- Add CI/CD:
"Set up GitHub Actions for automated testing" - Add accessibility testing:
"Add axe-core accessibility testing" - Add API testing:
"Help me test my REST API alongside UI tests" - Optimize performance:
"Show me advanced optimization patterns"
How It Works
When you ask Copilot to help with Playwright testing:
- You: "Help me analyze my app for testing"
- Copilot: Calls the
analyze-apptool - Tool: Returns detailed instructions to Copilot
- Copilot: Executes the instructions (detects stack, browses pages, creates files)
- You see: "ā Analysis complete! Created project-config.md, pages.md..."
You see results, not prompts. The tools provide Copilot with expert-level instructions that it follows automatically.
Example Workflow
# In your app project, ask Copilot:
"Help me set up Playwright testing for this app"
# Copilot will:
# 1. Call analyze-app ā detect stack, browse pages
# 2. Call generate-test-plan ā create test scenarios
# 3. Call setup-infrastructure ā create config and fixtures
# 4. Call generate-page-objects ā create page models
# 5. Call implement-test-suite ā write actual tests
All workflow documentation files are created in .playwright-wizard-mcp/ folder in your project root:
project-config.md- Detected tech stackpages.md- Page analysis with DOM quality scoresselector-strategy.md- Selector approach per pagetest-plan.md- Test suites with progress tracking
Note: The
.playwright-wizard-mcp/folder is for workflow tracking only. You may want to add it to.gitignore.
Tools
- get-architecture - Get the prompt architecture documentation
Requirements
- Node.js >= 18
- MCP-compatible client (GitHub Copilot, Claude Desktop, Cline, etc.)
Development
# Clone the repository
git clone https://github.com/oguzc/playwright-wizard-mcp.git
cd playwright-wizard-mcp
# Install dependencies
npm install
# Build
npm run build
# Run in development mode
npm run dev
Contributing
Contributions welcome! Please open an issue or PR.
License
MIT
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
