MCP & A2A – Model Context Protocol & Agent to Agent Protocol

Course Overview

This course teaches MCP and A2A protocols with practical implementation using Python, LangGraph, Streamlit, and Gemini APIs. You will learn how AI agents communicate, interact, and work together through MCP and Agent-to-Agent workflows.

Course Details

• Rating: 4.3 / 5
• Duration: 14 Hours
• Articles: 40
• Resources: 5 Downloadable Files
• Language: English
• Certificate: Included
• Access: Full Lifetime Access

What You Will Learn

• Understand MCP version 2 updates and architecture
• Learn Agent-to-Agent (A2A) communication workflows
• Build MCP clients and MCP servers from scratch
• Connect multiple AI agents using A2A protocol
• Create Streamlit UI applications for MCP systems
• Deploy MCP servers on Google Cloud using SSE
• Work with LangGraph and Gemini APIs
• Build orchestrator agents combining MCP and A2A systems
• Develop AI workflows using Python and modern AI tools

MCP Bootcamp: Build, Deploy & Secure Model Context Protocol

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Main Topics Covered

• Model Context Protocol (MCP)
• Agent-to-Agent Communication
• MCP Server Development
• LangGraph Workflows
• Streamlit UI Development
• Cloud Deployment

Who Should Learn This Course

• Developers exploring AI agents
• Students learning MCP and A2A protocols
• AI engineers building agent workflows
• Anyone interested in AI communication systems

Final Review

A hands-on course for learning MCP and A2A systems with real AI agent implementations. It is suitable for learners who want practical experience building connected AI workflows and multi-agent systems.