MCP Crash Course: Complete Model Context Protocol in a Day
What you'll learn
- Model Context Protocol (MCP) Theory
- Model Context Protocol (MCP) Servers
- Model Context Protocol (MCP) Clients
- Model Context Protocol (MCP) Tools, Resources, Prompts
- MCP Security
Requirements
- Knowledge in the GenAI Ecosystem is a MUST
- Software Engineering Experience is a MUST
- NodeJS installed
- Python Installed
- Claude Desktop Installed
- Cursor Installed
Description
This course contains the use of artificial intelligence :)
Please note that this is not a course for beginners. This course assumes that you have a background in software engineering and are proficient in Python. I will be using Cursor IDE but you can use any editor you'd like since we only use basic feature of the IDE like debugging and running scripts .
Ideal students are software developers / data scientists
What is the Model Context Protocol?
The Model Context Protocol (MCP) is an open-source standard, introduced by Anthropic in 2024, that allows AI models to seamlessly connect with external data sources, tools, and software systems
Architecture Components
MCP Hosts: Programs like Claude Desktop, Cursor, Windsurf, or AI tools that want to access data through MCP
MCP Clients: Protocol clients that maintain 1:1 connections with servers (Content ETA April)
MCP Servers: Lightweight programs that each expose specific capabilities through the standardized Model Context Protocol
Local Data Sources: Your computer's files, databases, and services that MCP servers can securely access (Content ETA End of March)
Remote Services: External systems available over the internet (e.g., through APIs) that MCP servers can connect to
(Content ETA End of March)Authenticaiton
Key Capabilities
Resources: Components that expose data and content from your servers to LLMs
Prompts: Functionality to create reusable prompt templates and workflows
Tools: Features that enable LLMs to perform actions through your server
Sampling: Capability that lets your servers request completions from LLMs
Transports: MCP's communication mechanism between clients and servers
Topic Covered:
MCP + Agent Security best practices
Containerizing MCP Servers
Protocol Flow
MCP + Docker
MCP + LangChain
OAuth 2.0 with MCP featuring Auth0
MCP Deployment (featuring Cloudflare)
A2A - Agent 2 Agent Protocol (WIP)
Who this course is for:
- Advanced GenAI Users
- Data Scientists
- Application Developers
- AI Engineers
Instructor
I’m a passionate Software Engineer with years of experience in back-end development and cloud architecture. I was one of the first engineers at Orca Security, where I helped shape the company’s core technology, and today I work as a GenAI Architect at Google Cloud, helping organizations design and deploy advanced generative AI and cloud-native solutions.
I’m also proud to be a LangChain Ambassador, actively contributing to the open-source community and helping developers build powerful LLM applications using the LangChain ecosystem.
I hold a Bachelor’s degree in Computer Science from the Technion, and I’ve always had a deep passion for teaching and mentorship. I taught Functional Programming and Introduction to Computer Science at Reichman University, where I guided the next generation of software engineers.
My courses are built on real-world experience and designed to give you practical, production-ready skills