MCP Bootcamp: Master Model Context Protocol with Python & JS
What you'll learn
- Understand the Agentic Theory behind Model Context Protocol and what Problems MCP Solves
- Master the architecture, concepts, and features of Model Context Protocol for production applications
- Deploy MCP Servics to Production
- Integrate MCP Services into LangGraph, LangChain and LangSmith
- Secure MCP Services using OAuth
- Learn how to find and use MCP for Virtually Every Use Case
- Implement and integrate a functional MCP server with real-time data providing capabilities
- Learn about what's coming up in the MCP world
- MCP using OpenAI's Agents Framework and Responses API
- Dockerizing MCP for Production
- Interviews with Industry Experts
Requirements
- Basic programming knowledge required. Familiarity with Python is required. No prior AI or MCP experience needed - we'll teach you everything from the ground up.
- Access to a PC/Mac where you can install Software like Claude, Cursor and Visual Studio Code
Description
If you want to Understand, Integrate, Implement, Publish and Secure and Deploy Model Context Protocol (MCP) solutions to Production, this course is for you.
It delivers what many others don't - genuine hands-on experience developing, integrating and deploying MCPs for AI applications. You'll walk away with both the conceptual understanding and practical tools to tackle real-world Model Context Protocol challenges.
Feedback from Students:
"The course structure works brilliantly*, starting with essential MCP foundations and methodically building toward practical applications." - Daniel
"Zoltan does a great job at breaking down the Model Context Protocol concepts so it's easy to learn and build up your knowledge as you go." - Jose
"Although I had some exposure to AI agents before, I still learned a lot about MCPs that I can use in my daily work. - Stefan
Why Model Context Protocol (MCP) matters: MCPs solve a critical problem in the multi-LLM world by creating standardized ways for AI models to interact with external systems. This MCP bootcamp takes you from fundamental Model Context Protocol concepts and third-party MCP integration to implementation of real-world projects at every step.
Course Structure: This course follows a hands-on, practical approach to Model Context Protocol. We start with the theoretical foundations to understand MCPs in context, then quickly move to building real working MCP applications.
THEORETICAL SECTION:
How LLM interactions and tool calling work with MCPs
The problem Model Context Protocol solves in a multi-LLM world
Core MCP concepts and architecture
Model Context Protocol features: Tools, Prompts, and more
Where MCPs fit in the AI ecosystem
PRACTICAL SECTION:
Complete MCP development environment setup for Mac & Windows
Working with MCP hubs and global providers
Integrating Model Context Protocol with Claude and Cursor
Step-by-step creation of your own Crypto Price MCP
Working with MCP Tools and Resources
Testing and debugging MCPs with MCP Inspector
Integrating Model Context Protocol into LangChain, LangGraph and LangSmith
Building Python and Javascript-based MCPs
Deploying Model Context Protocol solutions to Production
Securing MCPs with OAuth
Deploying Secure Model Context Protocol to OAuth Workers
HERO SECTION
Integrating MCPs with OpenAI Agents and the Responses API
Dockerizing MCPs and Docker-based Production Deployment
OUTLOOK
A sneak peek into Anthropic's MCP Roadmap about the future of Model Context Protocol
Join developers and AI enthusiasts already mastering MCP and transform your AI development skills with Model Context Protocol today!
Who this course is for:
- AI Enthusiasts who want to get hands-on with MCPs
- Software developers looking to enhance applications with AI capabilities
- AI Engineers
Instructor
- 4.6 Instructor Rating
- 8,744 Reviews
- 55,991 Students
- 3 Courses
I help global companies build web-scale data analytics and AI systems. Backed by 20+ years of experience in developing data-intensive applications, I spend most of my time helping companies kick-off and mature their data analytics and AI infrastructure, and give Cloud, Apache Spark, Databricks and MLOps courses regularly.
Earlier I helped Fortune 500 companies as a Principal Instructor and Consultant at Databricks. I built Prezi's (and SF startup's) big data analytics infrastructure, later led Prezi’s data engineering team, scaling it to serve 60 million users backed by a data volume over a petabyte. I also worked on kicking off the Spark integration component in RapidMiner, a global leader in predictive analytics.
Besides working with data analytics architectures, I enjoy teaching at Central European University, one of the best independent universities in Europe, and delivering courses and professional services engagements on behalf of Databricks, the company created by the original authors of Spark.