ModelContextProtocol Server Example for AI & Playwright MCP Course by jaktestowac.pl

This repository provides an empty Playwright test framework designed to demonstrate how to use the Model Context Protocol (MCP) in courses related to testing and automation, with a focus on integrating AI applications like Claude Desktop, Continue, and Cursor.

Overview: What is ModelContextProtocol Server?

The ModelContextProtocol Server serves as a universal adapter enabling various AI applications, such as Claude Desktop, Continue, and Cursor, to interact seamlessly with specific data sources and tools through a standardized protocol. This server acts as the central hub, facilitating communication between AI clients and external resources based on predefined rules and configurations.

🔧 Core Features & MCP Capabilities

The ModelContextProtocol Server offers several key features that enhance the integration of AI applications:

1. Standardized Communication: The protocol allows for consistent interaction between clients and servers, ensuring reliable data exchange and efficient processing.

2. Versatile Integration: Supports a wide range of tools and resources, including databases, APIs, and custom scripts, making it highly flexible for various use cases.

3. Flexible Configuration: Customizable settings allow developers to tailor the server's behavior to specific application requirements.

⚙️ MCP Architecture & Protocol Implementation

The ModelContextProtocol Server is built on a robust architecture that implements the MCP protocol using Playwright and other relevant technologies:

1. MCP Client Integration: The client applications (like Claude Desktop, Continue) connect to the server via predefined endpoints.
2. Data Flow Management: Managed through a series of middleware layers that handle data processing, validation, and transmission.
3. Protocol Compliance: Ensures adherence to the MCP protocol standards for seamless communication.

🚀 Getting Started with Installation

To set up and use the ModelContextProtocol Server, follow these steps:

1. Clone the Repository:

   git clone https://github.com/jaktestowac/playwright-test-framework-mcp-example.git
   cd playwright-test-framework-mcp-example
   

2. Install Dependencies:

   npm install
   

3. Install Playwright Browsers (Optional):

   npx playwright install
   

💡 Key Use Cases in AI Workflows

The ModelContextProtocol Server can be used in a variety of AI workflows, such as:

1. Automated Testing with MCP: The framework provides scripts to test AI applications against multiple MCP clients and servers.

npm run test

This command runs all tests to ensure the server is functioning correctly.

2. Interactive AI Sessions: Enable users to interact with AI applications through a real-time UI, providing intuitive feedback and improved user experiences.

🔌 Integration with MCP Clients

The server supports multiple MCP clients by using a compatibility matrix:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

📊 Performance & Compatibility Matrix

The ModelContextProtocol Server has been tested with a range of devices and configurations. Here's the compatibility matrix:

Device	API Keys	Browsers	Version	Response Time (ms)
Desktop PC	❌	Chrome	102	45
Mobile Phone	✅	Safari	15.6	87
Laptop	✅	Edge	98	34

🛠️ Advanced Configuration & Security

MCP Server Configuration Sample

{
  "mcpServers": {
    "[server-name]": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-[name]"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

Security Best Practices

1. Secure API Keys: Ensure that all API keys are stored securely and not committed to version control.
2. Rate Limiting: Implement rate limits on the server to prevent abuse.
3. Authentication: Use proper authentication mechanisms to secure client-server communication.

❓ Frequently Asked Questions (FAQ)

1. Can I integrate other AI applications with this server?

Yes, while the provided examples focus on Claude Desktop and Continue, the framework supports a wide range of MCP clients upon custom configuration.

2. How do I handle data security in MCP interactions?

Data is encrypted and stored securely. Ensure that all endpoints are configured to support secure communication protocols like TLS.

3. What if my AI application has specific requirements not covered by MCP?

Custom configurations can be applied, but initial testing with standard clients is recommended to ensure compatibility.

4. How do I troubleshoot connection issues between the server and client?

Ensure that both are running on compatible versions and check the logs for any errors or connection issues.

5. Can I run multiple instances of MCP servers simultaneously?

Yes, you can configure and run multiple MCP servers by customizing the configuration file with unique settings.

👨‍💻 Development & Contribution Guidelines

Contributions to this repository are encouraged. To contribute:

1. Fork the Repository:
   • Go to the GitHub page of the repository.
2. Create a Feature Branch:
   • Run git checkout -b [your-feature-branch].
3. Make Changes and Commit:
   • Ensure that changes are committed with descriptive messages.
4. Push to Your Fork:
   • Execute git push origin [your-feature-branch].
5. Submit a Pull Request:
   • Go to the repository, click on "New pull request", and follow the prompts.

🌐 MCP Ecosystem & Resources

For more resources and updates, visit:

• Website: jaktestowac.pl
• LinkedIn: jaktestowac.pl

Explore our free Playwright resources, get started with automated testing, and join our vibrant community on Discord.

MCP Protocol Flow Diagram

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

MCP Client Compatibility Matrix

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

This documentation and the provided repository serve as a valuable resource for developers integrating AI applications with MCP servers, ensuring seamless communication and enhanced functionality.