MCP: Build Agents with Claude, Cursor, Flowise, Python & n8n (Udemy.com)
AI Automation & Agents the with Model Context Protocol – Python, n8n, LangChain, Server, Client, Prompts, Tools & RAG
Created by: Arnold Oberleiter
Last updated July 2026
What you will learn
- Introduction to the Model Context Protocol (MCP): Practical tips to get started with the course and how LLMs can be extended using tools, prompts, and resources
- MCP Basics & Tool Integration in Claude Desktop: Understand the JSON structure, compare server types, set up with Node.js, and install via the MCP Installer
- Build Your Own Workflows in Claude Desktop: Access local applications, integrate databases, and connect API keys for secure interactions
- Connect MCP with Cursor & Vibe Coding: Install Python via pyenv, understand the Cursor interface, connect to OpenAI or Claude, and use MCPs flexibly
- API Keys & Access Control: Setup for OpenAI, OpenRouter & more, understand pricing differences, limitations, and project setup within Cursor
- Host Your Own MCP Server in n8n: Install Node.js, cover basics like triggers and actions, understand MCP client vs. host, and configure your server securely
How it compares
Against the other 461 rated Udemy courses in Data Science on CourseDuck:
- Rating4.6 out of 5higher than 67% of them
- Reviews309#292 of 462 by number of reviews
- Length13.5 hourslonger than 67% of them
- Last updatedJuly 2026more recently than 81% of them
Course Description
The Model Context Protocol (MCP) is one of the most exciting new technologies in AI automation and agent development.
Because Large Language Models (LLMs) need more than just prompts — they need context, tools, and external resources.
With MCP, you can provide exactly that.
But how does it work in practice?
How do you build your own MCP servers?
How do you use clients like Claude Desktop, Cursor, Windsurf, n8n or Flowise?
And how can you automate, secure, and integrate it all into your own AI project?
In this course, you'll learn exactly that – step by step, clearly explained, with many examples and ready-to-use workflows.
Fundamentals: Understand and Use the Model Context Protocol
Get a comprehensive overview of the MCP concept, how it works, and where to apply it
Learn how tools, prompts, and resources can be connected to LLMs like Claude, GPT, or Gemini using MCP
Start with practical tips, materials, and a dedicated course hub full of resources and curated references
Understand the key principles of prompt engineering and how system prompts work in the MCP context
Integrate MCP in Claude Desktop & Set Up Your First Servers
Install Claude Desktop using Node.js and NVM and configure your first server structures
Use JSON files and the official MCP installer to connect tools, databases, or your own APIs
Understand different server types (tool servers, prompt servers, database MCPs) and their use cases
Connect Claude Desktop with your local system or online services and enable API key–protected access
Install Python using pyenv and set up the UV package manager for running your first local MCP server
Combine MCP with Cursor, Vibe Coding & Python
Set up Cursor as a flexible client, connect it to existing MCP servers (e.g., Zapier), and explore its limitations and strengths
Use Vibe Coding and Python-based configurations to customize your MCP structure
Manage API keys efficiently, understand pricing structures, and build your own cross-tool MCP setup
Create, Host & Automate MCP Servers with n8n
Learn how to install and configure n8n locally and use it as a full-featured MCP platform
Create triggers and actions, and use custom nodes to connect Claude, Cursor, GitHub, or Google Drive
Integrate Pinecone and other vector databases for RAG agents directly into your MCP server
Learn how to host MCP servers on a VPS and keep them running 24/7 with secure access
Use authentication options and GDPR-compliant hosting strategies for secure deployments
Use MCP in Flowise, LangChain & LangGraph
Install Flowise and build complex tool workflows (email, calendar, Airtable, web search) using Agent V2
Use LangGraph to manage multi-step agent processes with clear role separation and tool execution
Manage Pinecone databases via SQLite, combine LangChain functionality, and build scalable automations
Explore the Flowise interface and create your own assistants with full MCP integration
Creative Projects & Specialized Workflows with MCP
Build voice interfaces for your LLM and control your AI through speech input using MCP
Automate 3D workflows in Blender with Claude, Python, and your own MCP server
Use the OpenAI API with n8n to generate images automatically
Share ideas with the community and explore creative or unconventional use cases
Develop Your Own MCP Servers in Python
Learn how to write MCP servers using Python and TypeScript – including prompt handling, tool integration, and resources
Use the modelcontextprotocol Python SDK to develop your own Claude-compatible prompt templates
Use the MCP Inspector for debugging and diagnostics, and expand your setup with Server-Sent Events (SSE)
Understand all transport types for MCP: STDIO, SSE, and Streamable HTTP – when and how to use them
Publish your MCP server on GitHub and explore hosting options like Cloudflare, AWS, or Azure
Avoid common mistakes and apply best practices for stable, secure server development
Security, Privacy & Legal Foundations
Recognize and understand threats like tool poisoning, jailbreaks, prompt injections, and MCP rug pulls
Secure your MCP server with API keys, authentication, and proper access control
Understand key data privacy regulations like GDPR and the EU AI Act, and address the challenges of hosting generative AI
Learn from real-world examples and get clear guidance on how to stay legally and technically compliant
After the course…
You will be able to build, host, develop, and integrate MCP-based agents into tools like Claude, n8n, Cursor, or Flowise.
You will know how to create secure MCP servers, combine them for your own projects, and even offer them as a service.
Whether for business or personal ideas – this course gives you full control over the MCP ecosystem.
Instructor Details
- 4.6 Rating
309 Reviews
Arnold Oberleiter
English text below the German text!
Hallo zusammen,
Ich bin Arnold "Arnie" Oberleiter, Dozent im Bereich Künstliche Intelligenz.
Es ist mein Ziel, mein Wissen und meine Begeisterung für KI mit euch zu teilen.
Ich glaube fest daran, dass ein tiefes Verständnis von KI einen enormen Vorteil in unserer technologiegetriebenen Welt bietet. Ich befasse mich mit LLMs (die Technologie hinter ChatGPT) bereits seit 2018-2019, als es mit Transformer & DIffusion losging.
Arnie
English:
Hi everyone,
I’m Arnold “Arnie” Oberleiter, an instructor in the field of artificial intelligence.
My goal is to share my knowledge and enthusiasm for AI with you.
I strongly believe that a deep understanding of AI offers a huge advantage in our technology-driven world. I’ve been working with LLMs — the technology behind ChatGPT — since 2018–2019, back when Transformers and diffusion models started taking off.
Arnie
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Reviews
By Akintayo Akinyemi on 2/16/2026
Very very good course, the instructor knows what he's talking about and he explained in many ways how to use mcp or create workflows and even how to host the mcp server . He gave a real good overveiw of the MCP, Workflows,Build Agent and the Eco systems of Agents/Tools/MCP/Flowise. I will highly recommend this course to anyone who want to know about n8n,mcp server, building Agnet Tools/workflows! Thank you for making a learning Video like this! Akintayo
By Viorel Mirea on 1/7/2026
This is one of the most comprehensive and practical introductions to the Model Context Protocol (MCP) I’ve seen so far. It doesn’t just explain what MCP is, but actually walks you through using it with Claude Desktop, Cursor, n8n, Flowise, LangChain, LangGraph, Python servers, and vector databases for RAG. I really appreciated the end-to-end, hands-on nature of the course: you build real MCP servers, connect real tools, and see how the whole ecosystem fits together. If you’re the kind of person who learns by building and experimenting, this course gives you a lot of usable material and a very good mental model of how MCP works in practice. That said, the course is very broad, and sometimes depth is traded for coverage. A bit more time on MCP internals, architecture, and production-grade patterns (multi-tenant, scaling, etc.) would make it even stronger. Also, as with any fast-moving AI tooling, some steps can lag behind recent updates. Still, as a practical, up-to-date, and implementation-focused entry point into the MCP ecosystem, this is excellent value and a great starting point if you want to seriously work with MCP.
By Ankit Vats on 1/5/2026
Really Comprehensive learning, from basic to advanced. Really brilliant teacher, Example Specially when you create mistake "JSAON"--> "JSON" it just embed in memory, Very explanatory and with practical examples
By Marcos Blanco on 12/12/2025
Fue bastante avarcativo, por lo que como un overview fue muy util, obviamente me sirvio para aprender mas en prfundidad que es un MCP como aplicarlo y las diferentes formas de uso, pero al avarcar mucho le falto detalle de varios puntos. igual me sirvio, ahora tengo mucho mas claro los conceptos y tengo material para seguir investigando. Gracias!!!
By Pedro Ribeiro Da Costa on 10/23/2025
Arnie is a great instructor, shows real practical knowledge about the topics he covers and, the occasional pun makes it that much fun! Thanks Arnie!
By Anonymized User on 9/9/2025
the course content is good. but a very important suggestion from my side is, please speak a little slow, because if we follow the steps its really tough if you run that way. Need to decrease the speed and listen twice to follow correctly or else missing out steps. Moreover may be as MCP is updating very fast there are few issues, as for example in lecture 32 when we add the mcp server in the url , SSE is not there when we follow the steps. There are many small things like these. mostly MCP has updated those.
By Rubel Mozumder on 9/4/2025
Nice course; it provides a good grasp of the application of the MCP technology. However, it contains fewer theoretical explanations of the MCP architecture. It may also include the MCP architecture in detail. In some places, the description was unnecessarily repeated, like a syntax error from '{}'. The course was also intended for Windows users; nothing is mentioned for Linux users separately, especially what could be the alternative of the Claude desktop for Linux users. Overall, the course is worthwhile for new users in the realm of MCP.
By J H on 9/1/2025
Good conceptual overviews and basic implementations that helped make MCP make sense. Good examples to build off of without spending a bunch of time debugging or setting up accounts.
By Sean O'Toole on 7/9/2025
It's an easy to follow along course so far. It has the content I was looking for and is the right level for me.
By Chris Raczkowski on 6/17/2025
I have been super happy with every course I've taken with Arnie. He is an excellent instructor, and very practical in his approach. Within 5 minutes of receiving a promotional email that Arnie was offering this MCP course, I purchased it.
Quality Score
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Overall Score : 92 / 100












