Udemy
    •  
    •  
    •  
    •  
    •  
    •  
    •  
    •  
Subscribe
Turn what you know into an opportunity and reach millions around the world.
Learn More
Your cart is empty.
Keep shopping
MCP & A2A - Model Context Protocol & Agent to Agent Protocol
Rating: 4.2 out of 5(139 ratings)
1,829 students

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

New 2026 Updates for MCP version 2 | Build 6 MCP Clients, 4 Servers, UI | Connect 3 Agents via A2A | FREE Gemini Key
Created byKartik Marwah
Last updated 2/2026
English

What you'll learn

  • MCP 2026 updates added to course for MCP Server & Client
  • You will learn Agent to Agent (A2A) Protocol - Connect 3 agents via A2A and build a host orchestrator agent with A2A + MCP
  • You'll build 5 MCP Clients and 3 MCP Servers from Scratch. Full Working Code Included!
  • Build a UI for MCP client in Streamlit in Python
  • Learn to deploy your MCP Server to Google Cloud using Server Sent Events (SSE)
  • We'll use a free Gemini API Key, so you don't need to pay for AI Models when learning!
  • We'll use Python, Gemini, LangGraph, SSE, Streamlit on MacOS

Course content

28 sections • 230 lectures • 14h 46m total length

  • What you will learn in this course?7:55
  • MCP Overview - What is Model Context Protocol?4:36
  • Can you answer these MCP basics?
  • New Upcoming MCP Version 2 2026 updates1:00
  • Note for Windows and Linux Users0:30

Requirements

  • Code WalkThroughs Included, no in-depth experience needed
  • Basic Python is a must
  • Basic familiarity with LLMs like Google Gemini/Claude
  • Course Recorded using MacOS. Windows Users can follow at their discretion

Description

NEW (FEB 2026) - MCP Version 2 updates added to course for MCP Server. Note that other updates are in progress! MCP is migrating to Version 2 by around end of March 2026. I am adding updates to the course to reflect those changes.


TLDR - In this course, you'll learn about MCP & A2A - Model Context Protocol & Agent2Agent Protocol. We will build 5 MCP Clients and 3 MCP Servers from Scratch. You'll build a UI for MCP client in Streamlit in Python. You'll learn to deploy your MCP Server to Google Cloud using Server Sent Events. To top it all, we'll use a free Gemini API Key from Google so you don't need to pay for AI Models when learning! We then build A2A Agents, Clients and Servers and use Google's ADK or Agent Development Kit. Integrate MCP + A2A together


Key Objectives of Course

  1. Use of MCP v2 (new update expected around end of March 2026)

  2. MCP Authentication - Sign in to MCP server with Google!

  3. Build A2A Servers, Clients and Agents (using Google's ADK or agent development kit) - in Beta

  4. Connect 3 Agents via A2A with full code implementation

  5. Build a Host Orchestrator agent - integrate with A2A + MCP

  6. A2A Python SDK

  7. Build 5 MCP Clients:

    1. #1. Basic Python + Gemini

    2. #2. LangGraph Based

    3. #3. LangGraph (with config.json)

    4. #4. Server Sent Events (SSE)

    5. #5. Streamlit MCP Client

    6. #6 Streamable HTTP Client

  8. Build 4 MCP Servers:

    1. #1 Python STDIO based

    2. #2 Python STDIO (with Docker)

    3. #3 Server Sent Event (SSE) Server

    4. #4 Streamable HTTP Server

  9. Connect your server to Claude Desktop

  10. Deploy MCP Server on Google Cloud Platform. Yes, you heard that right :)

  11. Build Streamlit UI for MCP Client in Python

  12. Avoid AI Costs using a free Gemini API Key: to work with Gemini API, Tools and Function calling


Detailed Course Description


Learn basics of MCP

In this hands-on course, you will gain a solid foundation in the Model Context Protocol (MCP) and its bidirectional client-server architecture. We begin by exploring the fundamentals of MCP, equipping you with the conceptual understanding needed to work confidently with this powerful protocol.

Next, you will implement your own MCP server in Python, hosted on a MacBook. This server will be connected to Claude Desktop, showcasing how you can interact with external tools. As part of this quick start, you'll build and test a tool that executes terminal commands via MCP using Claude Desktop.

Building on this foundation, we’ll guide you through developing your own MCP client in Python, integrating it with Google’s Gemini API. With a free Gemini API Key from Google, you’ll connect your client to your MCP server and perform tool invocations just like Claude Desktop.

By the end of this course, you will:

  • Understand the basic architecture and flow of MCP

  • Learn to build and run an MCP server using Python

  • Connect your custom MCP server to Claude Desktop

  • Obtain and configure a free Google Gemini API Key

  • Develop your own Python-based MCP client powered by Google Gemini

  • Test the interaction between your client and server to run real commands

What This Course Does Not Cover:

  • Advanced MCP primitives beyond tool-calling (for now, we focus only on tool invocation)

  • Windows-specific setup: While many steps are applicable across platforms, this course uses a MacBook for demonstrations. Windows users may follow along at their discretion.

Important Notes:

  • This course uses tools, APIs, Keys and services provided by third-party companies and open source projects. We do not offer any warranties or guarantees related to these services. Learners are responsible for understanding and agreeing to the terms and policies of each provider.

  • While many resources exist in fragments across the web, this course brings everything together in a streamlined, tested, and learner-friendly format based on real-world implementations.

  • Disclaimer

    The information provided in this course is for educational purposes only.

    Please be advised that when creating a Google account, Google Cloud Platform (GCP) project, using the Gemini API Key or using any other third-party account or service, you are solely responsible for reviewing and understanding the applicable terms and conditions, privacy policies, pricing, usage limits, and any other relevant policies or charges associated with that service.

    The instructor, course provider, and any affiliated parties do not provide any guarantees, warranties, or representations regarding the accuracy, completeness, or current applicability of any third-party services mentioned in this course, including but not limited to Google Cloud's $300 credit offer and the free Gemini API Key. Policies and offerings may change at any time without notice, and the information in this course may become outdated.

    By proceeding to create and use any such account or service, you agree that you do so at your own discretion and risk. The instructor and related parties shall not be held liable for any losses, charges, damages, liabilities, or consequences arising from your use or attempted use of such services.

    Always exercise independent judgment and due diligence before engaging with any third-party platform or offer. The credits and key from Google are available from Google irrespective of whether you take this course or not. We use them to help students setup and learn about MCP and AI without incurring cloud/AI costs.

Whether you're a developer, tinkerer, or AI enthusiast, this course will empower you to build practical systems using cutting-edge AI and modern protocol design.

Who this course is for:

  • Take this course if you want to code MCP Clients, Servers and User Interfaces
  • AI Agent Developers, Software Engineers, LangChain Developers
  • Entrepreneurs looking for a QuickStart on MCP

Report abuse