Model Context Protocol: Develop AI Agents with Python, n8n & LangChain – Servers, Clients, Tools, Resources & Prompts

What you'll 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

Extend the n8n MCP Server: Connect to Claude, Cursor, or GitHub nodes, integrate Zapier functionality for free, and add your own tools

Integrate Vector Databases into MCP: Manage Pinecone automatically via Google Drive, export workflows, and build RAG agents with vector search

HTTP Integration & GDPR-Compliant Hosting: Send HTTP requests to the MCP server even without an official MCP, learn hosting best practices

Use MCP in Flowise, LangChain & LangGraph: Install Flowise, understand the interface, compare agent platforms, and see real-world use cases

Tool Agents with MCP: Integrate access to emails, calendars, Airtable, web scraping, and Pinecone in Flowise for scalable automation

Flowise AI Agents V2 & New Features: Use LangGraph, work with SQLite as a record manager, and combine tool agents with vector access

Create Specialized Workflows with MCP: Voice control for LLMs, automations in Blender, custom image generation via OpenAI & n8n workflows

Develop Your Own Python MCP Server: Learn server programming basics, understand the GitHub repo, integrate tools, and use the MCP Inspector

Define Your Own Prompt Templates & Resources: Use the modelcontextprotocol Python SDK to manage custom prompts and data structures, and connect them to Claude

Build SSE Endpoints for the MCP Server: Enable real-time connections, trigger custom tools via events, and avoid common server development errors

Understand & Prevent MCP Security Risks: Recognize and mitigate tool poisoning, MCP rug pulls, jailbreaks, and prompt injections with secure strategies

Privacy, GDPR & Legal Frameworks for MCP: Know your rights and responsibilities when hosting, processing data, and using LLM tools in compliance with the law

Requirements

No prior knowledge required – everything is explained step by step.

Description

The Model Context Protocol (MCP) is one of the most exciting new technologies in AI automation and agent development.Because Large Language Models 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 ProtocolGet a comprehensive overview of the MCP concept, how it works, and where to apply itLearn how tools, prompts, and resources can be connected to LLMs like Claude, GPT, or Gemini using MCPStart with practical tips, materials, and a dedicated course hub full of resources and curated referencesUnderstand the key principles of prompt engineering and how system prompts work in the MCP contextIntegrate MCP in Claude Desktop & Set Up Your First ServersInstall Claude Desktop using Node.js and NVM and configure your first server structuresUse JSON files and the official MCP installer to connect tools, databases, or your own APIsUnderstand different server types (tool servers, prompt servers, database MCPs) and their use casesConnect Claude Desktop with your local system or online services and enable API key–protected accessInstall Python using pyenv and set up the UV package manager for running your first local MCP serverCombine MCP with Cursor, Vibe Coding & PythonSet up Cursor as a flexible client, connect it to existing MCP servers (e.g., Zapier), and explore its limitations and strengthsUse Vibe Coding and Python-based configurations to customize your MCP structureManage API keys efficiently, understand pricing structures, and build your own cross-tool MCP setupCreate, Host & Automate MCP Servers with n8nLearn how to install and configure n8n locally and use it as a full-featured MCP platformCreate triggers and actions, and use custom nodes to connect Claude, Cursor, GitHub, or Google DriveIntegrate Pinecone and other vector databases for RAG agents directly into your MCP serverLearn how to host MCP servers on a VPS and keep them running 24/7 with secure accessUse authentication options and GDPR-compliant hosting strategies for secure deploymentsUse MCP in Flowise, LangChain & LangGraphInstall Flowise and build complex tool workflows (email, calendar, Airtable, web search) using Agent V2Use LangGraph to manage multi-step agent processes with clear role separation and tool executionManage Pinecone databases via SQLite, combine LangChain functionality, and build scalable automationsExplore the Flowise interface and create your own assistants with full MCP integrationCreative Projects & Specialized Workflows with MCPBuild voice interfaces for your LLM and control your AI through speech input using MCPAutomate 3D workflows in Blender with Claude, Python, and your own MCP serverUse the OpenAI API with n8n to generate images automaticallyShare ideas with the community and explore creative or unconventional use casesDevelop Your Own MCP Servers in PythonLearn how to write MCP servers using Python and TypeScript – including prompt handling, tool integration, and resourcesUse the modelcontextprotocol Python SDK to develop your own Claude-compatible prompt templatesUse 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 themPublish your MCP server on GitHub and explore hosting options like Cloudflare, AWS, or AzureAvoid common mistakes and apply best practices for stable, secure server developmentSecurity, Privacy & Legal FoundationsRecognize and understand threats like tool poisoning, jailbreaks, prompt injections, and MCP rug pullsSecure your MCP server with API keys, authentication, and proper access controlUnderstand key data privacy regulations like GDPR and the EU AI Act, and address the challenges of hosting generative AILearn from real-world examples and get clear guidance on how to stay legally and technically compliantAfter 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.

Overview

Section 1: Introduction – Overview, Tips & Understanding the Model Context Protocol

Lecture 1 Welcome

Lecture 2 Course Overview

Lecture 3 Important Tips for the Course

Lecture 4 Explanation of Course Links

Lecture 5 Key Resources

Lecture 6 Instructor Introduction: Arnold Oberleiter (Arnie)

Lecture 7 The Model Context Protocol Explained: Give LLMs Tools, Prompts & Resources

Lecture 8 Prompt Engineering Basics & System Prompts

Section 2: MCP Basics in Claude Desktop & the Setup: Node.js, Python & NVM Installation

Lecture 9 What You'll Learn in This Section on MCP Basics

Lecture 10 Model Context Protocol (MCP): Official Documentation Overview

Lecture 11 Setup: Install Node.js, nvm, VS Code and Claude Desktop Quickly

Lecture 12 Claude Desktop Interface & Settings Overview

Lecture 13 Integrate MCP into Claude Desktop via JSON File

Lecture 14 Set Up Multiple MCP Servers Easily with the MCP Installer + Debugging via Logs

Lecture 15 Installing Python, pyenv & the uv Package Manager

Lecture 16 Quick Tip: Discover More MCP Servers & Clients on GitHub, MCP.so & more

Lecture 17 Set Up API Key Integration for Your MCP Server

Lecture 18 Problems with MCP servers that are no longer maintained

Lecture 19 One of the best MCP servers and the problem with it

Lecture 20 Recap on Claude Desktop and MCP Basics What to Remember

Section 3: Integrating MCP in Cursor, Vibe Coding & API Keys

Lecture 21 What We'll Cover: Python, Cursor, Vibe Coding & API Keys

Lecture 22 Cursor Crash Course: Install, Explore the Interface & Start Vibe Coding

Lecture 23 Connect Cursor to Any MCP Server: Use Zapier for Free, GitHub, Slack & More

Lecture 24 Create API Keys: OpenAI API, OpenRouter, Pricing, Project Setup & Management

Lecture 25 Limitations of the Model Context Protocol with Cursor as a Client

Lecture 26 Recap on Cursor and MCP

Section 4: MCP in n8n – Create Your Own Server & Client: Hosting, Security & More

Lecture 27 What to Expect in the n8n & MCP Section

Lecture 28 Install n8n Locally with Node.js and Interface Overview

Lecture 29 Managing Node Versions (Fixing Errors in n8n Installation)

Lecture 30 Updating n8n Locally via Node.js

Lecture 31 n8n Basics: Triggers, Actions, Nodes, Models, MCP and More

Lecture 32 Create MCP Server in n8n and Use the Google Cloud Console

Lecture 33 Connect your n8n MCP Server to Various Hosts: Claude, Cursor, n8n, Windsurf

Lecture 34 Secure Your MCP Server Properly: Set Up Authentication

Lecture 35 Add Tools to Your MCP Server & Use Zapier for Free in Claude

Lecture 36 Automatically Create Pinecone Vector Database via Google Drive for n8n MCP

Lecture 37 Export & Import n8n Workflows Easily (JSON Format)

Lecture 38 Build a RAG Agent and Integrate Vector Database into the MCP Server

Lecture 39 How to Integrate Multiple Vector Databases into Your MCP Server

Lecture 40 Connect Any API in n8n Using the HTTP Request Node

Lecture 41 Self-Host n8n: Make Your MCP Server Accessible from Anywhere – Even for Others

Lecture 42 Connect Every MCP Server (GitHub or Python Servers) to n8n via Community Node

Lecture 43 n8n Community Node: Common Issues with Prompts & Resource

Lecture 44 Recap: What to Remember

Section 5: MCP in LangChain, LangGraph & Flowise

Lecture 45 What We'll Learn in This Section

Lecture 46 MCP in LangChain, LangGraph & Flowise: Key Differences

Lecture 47 Install Flowise locally with Node.js and Update It

Lecture 48 Flowise Interface & Marketplace: LangGraph Made Easy

Lecture 49 Tool Agent in Flowise with MCP: Emails, Calendar, Airtable, Web Search & More

Lecture 50 Pinecone Vector Database in Tool Agents for RAG (with SQLite Record Manager)

Lecture 51 Flowise AI Agents V2 with MCP

Lecture 52 Integrate Custom SSE MCPs into Flowise and a Postgres Database

Lecture 53 More Possibilities in Flowise

Lecture 54 Hosting Flowise on Render: Step‑by‑Step and a quick HTML lesson

Lecture 55 Recap on MCP with LangChain and Flowise

Section 6: Special Workflows – Automations with Blender, Image Generation & More

Lecture 56 What We'll Cover in This Section

Lecture 57 Talk to Your LLM & MCP Server – How to Use Voice Input

Lecture 58 Automate Blender with MCP, Claude and Python and uvm

Lecture 59 Create an MCP Server with Memory: Persistent Context & Long-Term Recall

Lecture 60 Create an MCP Server for Image Generation (OpenAI API, n8n, Flux)

Lecture 61 Can ChatGPT Act as an MCP Host? Webhook & n8n Workaround Explained

Lecture 62 Connecting Flowise to n8n: Use HTTP Request & cURL Import

Lecture 63 Racap: Got Cool MCP Server or Workflow Ideas? Share Them With Us!

Section 7: Program Your Own MCP Server – Step by Step in Python

Lecture 64 What You'll Learn Here: Program MCP Servers with Python & TypeScript

Lecture 65 Project Overview: Python Code, Structure & GitHub Repository Explained

Lecture 66 Program an MCP Server in Python with Tools (Python SDK) & start MCP Inspector

Lecture 67 MCP Inspector: Debug & Analyze Your Python MCP Server via STDIO Transport

Lecture 68 Create a Config File for Your Python MCP Server to Enable Host Connections

Lecture 69 Add Resources to Your Python MCP Server (Vibe Coding with Cursor)

Lecture 70 Add Prompt Templates Using the modelcontextprotocol Python SDK

Lecture 71 Use Different Transport Methods: STDIO, SSE & Streamable HTTP

Lecture 72 More Possibilities: Tips & Common Mistakes in Custom Server Development

Lecture 73 How to Publish Your MCP Server on GitHub – Step by Step (and other options)

Lecture 74 Hosting Options for Your Server: VM Setup with Cloudflare, AWS, Azure & More

Lecture 75 Recap: What to Remember

Section 8: MCP Client (not needed for moste but here we go with a Overview)

Lecture 76 Developing MCP Clients

Section 9: Security, Privacy, GDPR & Common Issues with MCP

Lecture 77 What We'll Learn in This Section

Lecture 78 Simple Example of a Misbehaving Server (you got hacked)

Lecture 79 Tool Poisoning, MCP Rug Pulls & Other Security Vulnerabilities

Lecture 80 Common Attacks on LLMs: Jailbreaks, Prompt Injections & Data Poisoning

Lecture 81 Authentication and API Keys

Lecture 82 Avoid Accidental Deletion & Unwanted Full Access on Your Server

Lecture 83 Copyrights, Data Privacy, Censorship, License & Compliance

Lecture 84 Final Recap & My Thanks

Lecture 85 Bonus

AI developers, tech tinkerers, and automation nerds who want to understand the Model Context Protocol (MCP), build their own servers, or extend existing clients like Claude, Cursor, n8n, or Flowise.,Private individuals and AI enthusiasts who finally want to understand how LLMs can be extended with tools, prompts, and resources – and get their first MCP agents up and running.,Entrepreneurs and freelancers looking to use MCP-based AI workflows to automate routine tasks, streamline processes, or build their own AI service offering.,Software developers & prompt engineers working at the intersection of LLM APIs, tool integration, and workflow automation who want to apply MCP to their own projects.,Tech-savvy individuals & AI newcomers who want to combine tools like Claude Desktop, Cursor, n8n, or Flowise and dive deep into the MCP ecosystem.