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Mastering MCP: Beginner to Pro Across the AI Ecosystem

Name: Mastering MCP: Beginner to Pro Across the AI Ecosystem
Rating: 4.5 (290 reviews)

LangChain, LlamaIndex, OpenAI SDK, Google ADK, Claude, Azure OpenAI & Gemini, Build your Own MCP Server, Docker , Gradio

Highest Rated

Created byKshitij Joy (Cloud Alchemy)

Last updated 11/2025

English

English [Auto],Dutch [Auto],

What you'll learn

What is Model Context Protocol ?
What is a Model / Context / Protocol ?
History & Transition to MCP
Key Features & Benefits of MCP
A Quick intro to Anthropic & Claude
Why the mention of Anthropic for MCP
How is it trending on Github Stars
Core Architecture of MCP
Key Components- Deep Dive
What is JSON-RPC 2.0 ?
MCP Transport Layer
Transport Mechanism - STDIO vs SSE
What is Claude Desktop
Demo using Claude Desktop
Enable Filesystem MCP Server in Claude
Enable Sqlite MCP Server in Claude
Working on the Pre-reqs for Future Lab Exercises
Langchain-Gemini-Sqlite MCP Server
LlamaIndex-Azure OpenAI-Filesystem MCP
OpenAI SDK & Azure MCP Server
Google ADK & Paypal MCP Server
Build your own MCP Server

Course content

13 sections • 122 lectures • 6h 50m total length

Title - Introduction to MCP0:08
What is MCP ?6:11
Discover the model context protocol (MCP) as an open, vendor-neutral standard that provides pre-built integrations, connecting AI models to external data sources via universal MCP servers.
What is a Model ?3:47
Explore what a model is in AI, from pattern and prediction to large language models like ChatGPT, and understand how transformers enable translation, summarization, and conversation.
What is Context ?2:59
What is a Protocol ?3:11
Explain how a protocol is a set of rules that governs machine communication, with MCP as an open, publicly accessible, vendor-neutral client-server standard that reduces duplication and fuels ecosystem growth.
Demo: Something that we shall build together5:20
History & Transition to MCP5:49
Key Features & Benefits of MCP6:57
Discover MCP features, including standardized integration and plug-and-play architecture, secure OAuth/TLS access, real-time data from databases and APIs, interoperability across AI models, and agentic workflows.
A Quick intro to Anthropic & Claude2:48
Explore Anthropic and its Claude product, and compare Claude to OpenAI. Learn about the Claude model family—haiku, sonnet, opus—and how cost and safety drive choices.
Why the mention of Anthropic for MCP4:26
Uncover how anthropic's model context protocol standardizes MCP to connect AI with data, tools, and servers. Leverage Python SDKs and cloud desktop integration to build open, interoperable AI workflows.
Adoption by Big Vendors3:21
How is it trending on Github Stars3:36
Explore how to gauge open-source popularity with GitHub star history from starhistory.com, and see MCP's rocket-like rise since November 2024 compared with Lama index, Lang graph, and OpenAI swarm.

Title - MCP Architecture0:08
Intro - MCP Architecture2:46
Explore the MCP architecture, a flexible client-server bridge built on json-rpc 2.0, with core components server, client, and transport layer, and transport options like stdio and streamable http.
Core Architecture of MCP5:06
Mastering MCP presents a client-server architecture where MCP clients initiate requests via a json rpc protocol, routing queries to servers that access local, remote, or web api data sources.
Key Components- Deep Dive7:04
Understand the MCP client–server architecture, where the server exposes tools, resources, and prompts, the client queries resources and invokes tools, guided by structured prompts and a clear flow.
What is JSON-RPC 2.05:36
MCP Transport Layer2:43
Transport Mechanism - STDIO3:41
Transport Mechanism - SSE3:36
Explains server sent events (sse) in the model context protocol (mcp), enabling server to client streaming over http for real time stock price updates and simple notifications in restricted networks.
Transport Mechanism - Streamable HTTP3:51

Title- MCP With Claude Desktop0:08
Master MCP from beginner to pro across the AI ecosystem, exploring how Claude Desktop supports MCP mastery.
What is Claude Desktop1:59
Discover how Claude Desktop, built on the MCP (model context protocol), is downloaded and used on macOS, Windows, and Arm64, with a Google login for quick access.
Demo using Claude Desktop3:01
Enable Filesystem MCP Server in Claude6:18
Sample Configuration

{
"mcpServers": {
"filesystem": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-filesystem",
"/Users/kshitijjoy_1/Desktop",
"/Users/kshitijjoy_1/Downloads"
]
}
Enable Sqlite MCP Server in Claude6:21
Sample Configuration

{
"mcpServers": {
"sqlite": {
"command": "uvx",
"args": ["mcp-server-sqlite", "--db-path", "/Users/kshitijjoy_1/test.db"]
},
"filesystem": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-filesystem",
"/Users/kshitijjoy_1/Desktop",
"/Users/kshitijjoy_1/Downloads"
]
}
}
}
Demo: Create your own MCP Server3:22
Demo: Quick Understanding of the Code4:33
Explore how to build a fast MCP server with a tool called what am I learning, using a decorator to register the MCP tool, and enable client interactions over stdio.
What is MCP Inspector ?4:15
MCP inspector is an interactive web-based dev tool for testing and debugging model context protocol servers, built with React, offering live exploration of resources, prompts, tools, and logs.
Demo: MCP Inspector3:24
Demo : Connect your MCP Server to Claude Desktop4:22
Connect your MCP server to Claude Desktop by configuring cloud settings, adding the server path, and exposing a tool to demonstrate tool calling and learning prompts.
Demo: Update Config.json in automated manner2:13

Title - Pre-Reqs for Lab Exercises0:08
Visual Studio Code - Article0:37
Demo: VsCode2:21
Install git - Article0:35
Demo: git2:45
Create Azure OpenAI Service & Deployment - Article1:07
Demo: Azure OpenAI Service and Deployment4:28
Get API Keys in Google, OpenAI , Azure OpenAI - Article0:43
Demo: Create API Keys in Google / OpenAI / Azure OpenAI3:40
Install nodejs, npm, npx - Article1:20
Demo: Installing nodejs/npm/npx5:10
Installing Azure CLI - Article0:31
Demo: Installing Azure CLI1:33
Install and verify Azure CLI on Windows, macOS, and Linux to enable authentication for the MCP server, using winget, brew, or curl and az commands.

Let's Get Connected !!0:23
Title - Langchain-Gemini-Sqlite MCP Server0:08
What is Langchain7:59
What is Langchain MCP Adapter6:03
Explore the long chain MCP adapter, which connects to an MCP server like a SQLite database, enabling natural language queries and tool wrapping for long chain and Lang graph.
Understand the Workflow4:23
Translate a natural language query into SQL using the MCP SQLite server. See how the Lang Chain MCP adapter enables Gemini to fetch tabular results.
Work on the Pre-reqs4:45
Demo: Project Setup and Install Packages4:31
Demo: Setup MCP Sqlite Server & Google API Key2:51
Demo: Understand the Code7:51
Demo: Run the Application3:24

Title - LlamaIndex-Azure OpenAI-Filesystem MCP0:08
What is LlamaIndex ?5:34
LangChain Vs Llamaindex4:38
Importance of MCPToolSpec4:20
Understand the Workflow5:04
Explore the file system MCP server workflow, using Lama index to orchestrate tool calls via the model context protocol with GPT four mini on Azure OpenAI, returning results.
Get an Understanding of Filesystem MCP Server2:46
Demo: Get an Understanding of Pre-reqs2:47
Prioritize prereqs like Python 3.8+, Node.js with npm, npx, and Azure OpenAI API access, then learn to obtain endpoints and API keys for your code.
Demo: Create Project Environment & Install Packages2:34
Set up the environment by creating a llama index MCP folder in Visual Studio Code, then initialize with uv init lama mcp and install llama index, Azure OpenAI packages.
Demo: Understanding the Code8:59
Demonstrates configuring a dot env with Azure OpenAI keys, endpoint, and version, deploying GPT-4 mini, and walking through the MCP tooling and memory setup in code.
Demo: Running the Code5:56

Title - OpenAI SDK & Azure MCP Server0:08
What is OpenAI Agents SDK3:52
What is Azure MCP Server ?3:25
Explore how Azure MCP server enables natural language interaction with Azure services through the OpenAI SDK, offering read-only operations for storage and cosmos db, with future read-write capabilities.
Understand the Workflow4:28
Demo: Work on the Pre-Reqs3:06
Demo: Project Setup & Install Packages2:17
Demo: Check Environment File & Ensure az cli works2:15
Validate the environment file and OpenAI API key, confirm the correct Python environment, then perform Azure CLI login and subscription selection before running the code.
Demo: Understanding the Code7:41
Demo: Running the Code3:08
Run the Azure MCP demo by executing the code in Visual Studio Code to start the MCP server and query storage accounts and resource groups in a formatted table.

Title - Google ADK & Paypal MCP Server0:08
What is Google ADK ?3:37
What is Paypal MCP Server ?2:19
Explore PayPal's MCP server from the remote mode using server-sent events, learn its tools, and see how to create a simple invoice via natural-language input.
Understand the workflow1:58
Explore the workflow and tech stack using Google ADK, Gemini LLM, and the PayPal MCP server to generate an invoice from natural language.
Demo: Pre-Reqs , Project Setup & Installing Packages5:19
Set up python 3.9+ and nodejs, configure a PayPal account with 2FA, initialize a google adk project, and prepare PayPal_agent with init.py, agent.py, and .env.
Demo: Understanding the Code4:58
Demo: Running the Code4:04
Launch the code with the ADK web interface, run a local server, and have the PayPal agent create an AI enablement invoice and email it.

Title - Build your Own MCP Server0:08
Build your own MCP server as part of mastering MCP across the AI ecosystem, designed for beginners to pros.
What we shall build together4:00
Demo: Pre-Reqs , Project Setup & Installing Packages3:02
Meet prereqs: Python 3.10+, Azure CLI with az login, and the UV package manager. Create a Visual Studio Code project folder and add Azure server.py with the environment file.
Set Environment & Python Code1:36
Demo : Understand the Code6:02
Build a lightweight MCP server to authenticate with Azure, load env vars, and create or update an Azure resource group with tags using the Azure SDK.
Demo: Run the MCP Server1:16
Demo: Test with MCP Inspector4:22
Demo: Test with Claude Desktop4:19
Demonstrates testing an MCP server via cloud desktop, using MCP install to generate config.json, then calling the external integration to create an Azure resource group in East US two.

Title - Build Your Own MCP Server - S-HTTP0:06
Intro to Streamable HTTP2:45
Demo : Setup the MCP Server on Local Environment4:08
Demo: Start MCP Server & Test with Inspector4:05
Start the MCP server and test with the inspector to verify streamable http on uvicorn 0.0.0.0:8000. Demonstrate creating a local resource group and plan production deployment on VM in Azure.
Demo : Provision a new VM in Azure3:05
Demo: Test the connectivity to VM and open ports3:08
Create Entra ID App Registration & Give Privileges4:36
Demo: Copy the Files from GitHub Repo to Remote Server5:03
Demo: Start the MCP Server Remotely2:09
Demo: Start the Inspector from your Machine3:05
Test a cloud-based MCP server running in an Azure VM from your local machine using the inspector to connect via IP: 8000 and validate remote resource creation.

Requirements

Basic Understanding of Generative AI
Basic Understanding of Python
Basic Understanding of Large Language Model (LLM)
How to use LLMs with Python
Understanding of Azure / Open AI / Google Gemini
Basic Understanding of AI Agents

Description

Description:

Dive into the evolving world of Model Context Protocol (MCP) and learn how to harness its full potential across today's leading AI frameworks and platforms.

This course is designed for learners of all levels — whether you're a no-code enthusiast or a Python developer — and takes you on a practical journey from foundational concepts to advanced integrations.

You'll explore how MCP is implemented and extended across top-tier AI platforms, gaining real-world experience with tools used by industry leaders.

What You'll Learn:

The Foundations of Model Context Protocol (MCP): Understand its role in building contextual, memory-aware AI systems.
No-Code to Pro-Code: Start with intuitive interfaces and transition into Python-based development.
LangChain: Build complex agent workflows and memory chains with MCP integration.
LlamaIndex: Implement Retrieval-Augmented Generation (RAG) pipelines for smarter context handling.
OpenAI Agents SDK: Use MCP in GPT-powered apps with advanced prompt engineering and session management.
Google ADK: Integrate Google’s tools with MCP-based workflows.
Claude (Anthropic): Work with high-context, safety-first AI models.
Azure OpenAI: Deploy MCP-powered models in enterprise-ready environments.
Gemini (Google DeepMind): Explore the cutting edge of multimodal MCP applications.

Who This Course is For:

No-code builders looking to level up with Python
Developers and engineers interested in cross-platform AI design
Product teams building memory-aware assistants or RAG systems
AI enthusiasts exploring advanced prompting, agents, and context management

By the end of this course, you’ll not only understand the core mechanics of MCP, but also know how to implement it across frameworks to build scalable, contextual, and intelligent AI systems.

Who this course is for:

Beginner to Model Context Protocol - MCP
Understand No-Code & Python Code for each Use Case
No-Code Enthusiasts & Citizen Developers
Machine Learning Engineers & AI Practitioners
Product Managers & Tech Leads

Mastering MCP: Beginner to Pro Across the AI Ecosystem

What you'll learn

Explore related topics

Course content

MCP Introduction12 lectures • 49min

MCP Architecture and Components9 lectures • 35min

Understand MCP using Claude Desktop11 lectures • 40min

Working on the Pre-reqs for Future Lab Exercises13 lectures • 25min

Langchain & MCP10 lectures • 42min

LlamaIndex & MCP10 lectures • 43min

OpenAI Agents SDK & MCP9 lectures • 30min

Google ADK & Paypal MCP Server7 lectures • 22min

Build your Own MCP Server8 lectures • 25min

Build your Own MCP Server - Streamable HTTP10 lectures • 32min

Requirements

Description

Who this course is for: