A2A MCP Playwright For Web Automation

Presenting a web automation agent with Google A2A Protocol and Model Context Protocol (MCP) and web automation. If you've ever wanted to control web browsers with natural language while staying compatible with modern AI agent protocols, this one's for you!
Think of it as a polyglot web automation server that can seamlessly integrate with any AI system, regardless of which protocol they're using!

🎯 The Project: Dual-Protocol Web Automation Agent

What makes this project special is its ability to handle both protocols simultaneously:

🤝 A2A Protocol Support
- Google's Agent-to-Agent protocol
- Standard JSON-RPC communication
- Task-based interaction model
🔄 MCP Protocol Support
- Model Context Protocol integration
- Direct LLM communication
- Context-aware interactions

Plus these awesome capabilities:

🤖 Control web browsers using natural language
📸 Take screenshots and extract text from web pages
🔌 Process requests via both A2A and MCP endpoints
🌐 Seamless protocol translation

Want to try it out? Check it here: https://vishalmysore-a2apw.hf.space/

🛠️ The Tech Stack

Here's what I used to bring this to life:

Backend ➡️ Java Spring Framework
Web Automation ➡️ Playwright
Protocol Support ➡️ a2ajava framework
API ➡️ JSON-RPC
Deployment ➡️ Docker + HuggingFace Spaces

🎢 The Journey: Challenges & Solutions

1. Protocol Integration Hell 😅

Challenge: Making A2A and MCP protocols play nice together was like trying to get cats and dogs to dance!

Solution: I created an abstraction layer that acts as a translator between protocols. Think of it as a diplomatic mediator that ensures everyone speaks the same language.

// Simplified example of the abstraction
public interface ProtocolHandler {
    Response processRequest(Request request);
    void validateMessage(Message message);
}

2. Browser Automation Reliability 🎭

Challenge: Web pages are like wild animals - unpredictable and constantly changing.

Solution: Implemented robust waiting mechanisms and retry logic. Here's a peek at the pattern:

await page.waitForSelector('.dynamic-content', {
    state: 'visible',
    timeout: 5000
});

3. Resource Management 🔄

Challenge: Browsers love to eat RAM for breakfast!

Solution: Implemented browser recycling and parallel execution management:

Pool of managed browser instances
Automatic cleanup of unused resources
Smart request queuing

💡 Key Learnings

Start Simple, Scale Later
- Begin with one protocol
- Add features incrementally
- Test extensively before adding complexity
Error Handling is Your Friend
- Implement comprehensive error handling early
- Use retry mechanisms wisely
- Log everything (you'll thank yourself later)
Performance Matters
- Browser instances are expensive
- Connection pooling is essential
- Resource cleanup is crucial

🚀 Quick Start Example

Want to try it out? Here's a simple example to extract text from a webpage:

curl -X POST \
-H "Content-Type: application/json" \
-d '{
    "method": "tools/call",
    "params": {
        "name": "browseWebAndReturnText",
        "arguments": {
            "provideAllValuesInPlainEnglish": "Go to Google.com, search for \"a2ajava\""
        }
    },
    "jsonrpc": "2.0",
    "id": 17
}' \
http://localhost:7860

🎓 Tips for Your Own Project

Architecture First
- Plan your protocol handling strategy
- Design with extensibility in mind
- Keep business logic separate from protocol handling
Testing is Crucial
- Test with different types of websites
- Verify protocol compliance
- Check resource management
Security Matters
- Validate URLs
- Implement rate limiting
- Handle browser security settings