Udemy – MCP: Build Agents with Claude, Cursor, Flowise, Python & n8n 2025-4

MCP Course: Build Agents with Claude, Cursor, Flowise, Python & n8n. This course teaches the Model Context Protocol (MCP), a cutting-edge technology in the field of AI automation and intelligent agent development. Participants learn how to build and integrate AI agents using tools such as Claude, Cursor, Flowise, Python and n8n. First, the basics of MCP are taught and how to connect tools, databases and external resources to Large Language Models (LLMs). Then, it covers setting up MCP servers with Node.js and Python, managing API keys and connecting to various services such as Claude Desktop and n8n. Next, it teaches how to integrate MCP with tools such as Cursor, Flowise and LangChain to build complex workflows. It also covers topics such as hosting servers on VPS, data security, GDPR compliance and developing creative projects with MCP. At the end, participants will be able to develop their own custom MCP servers, secure them, and deploy them in real projects.

What you will learn

• Introduction to Model Context Protocol (MCP): Practical tips for getting started and how to extend LLMs using tools, text inputs, and resources.
• MCP Basics and Tool Integration in Claude Desktop: You will understand JSON structure, compare server types, get started with Node.js, and install via MCP Installer.
• Build your own workflows in Claude Desktop: access local applications, integrate databases, and connect API keys for secure interactions.
• Connecting MCP with Cursor and Vibe Coding: You install Python via pyenv, understand the Cursor interface, connect to OpenAI or Claude, and use MCPs flexibly.
• API keys and access control: Getting started for OpenAI, OpenRouter, and more, understanding pricing differences, limitations, and setting up a project on Cursor.
• Hosting your own MCP server on n8n: You’ll install Node.js, cover the basics like triggers and actions, understand the difference between the MCP client and host, and configure your server securely.
• MCP n8n Server Expansion: Connect to Claude, Cursor or GitHub nodes, integrate Zapier functionality for free, and add your own tools.
• Integrate vector databases into MCP: Automatically manage Pinecone via Google Drive, export workflows, and build RAG agents with vector search.
• HTTP Integration and GDPR-Compliant Hosting: You will send HTTP requests to the MCP server even without an official MCP, learning hosting best practices.
• Using MCP in Flowise, LangChain and LangGraph: You install Flowise, understand the user interface, compare operating platforms and see real use cases.
• Tool Agents with MCP: Integrate access to emails, calendars, Airtable, web scraping, and Pinecone into Flowise for scalable automation.
• Flowise V2 AI Agents and 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, automation in Blender, custom image generation via OpenAI, and n8n workflows.
• Developing your own MCP Python server: You will learn the basics of server programming, understand the GitHub repository, integrate tools, and use the MCP Inspector.
• Define your own text input formats and resources: You use the modelcontextprotocol Python SDK to manage custom text inputs and data structures and connect them to Claude.
• Building SSE endpoints for MCP Server: Enable real-time connections, trigger custom tools via events, and avoid common server development errors.
• Understand and prevent MCP security risks: Identify and mitigate tool poisoning, MCP rug pulls, jailbreaks, and text input injection with secure strategies.
• Privacy, GDPR and Legal Frameworks for MCP: Know your rights and responsibilities when hosting, processing data and using LLM tools in compliance with the law.

This course is suitable for people who:

• AI developers, technology professionals, and automation enthusiasts who want to understand the Model Context Protocol (MCP), build their own servers, or extend existing clients like Claude, Cursor, n8n, or Flowise.
• Individuals and AI enthusiasts who finally want to understand how LLMs can be extended with tools, text inputs, and resources – and launch their first MCP agents.
• Entrepreneurs and freelancers looking to use MCP-based AI workflows to automate routine tasks, streamline processes, or offer their own AI services.
• Software developers and prompt engineers who work at the intersection of LLM APIs, tool integration, and workflow automation and want to apply MCP to their projects.
• Tech-savvy individuals and AI newcomers who want to combine tools like Claude Desktop, Cursor, n8n or Flowise and dive deep into the MCP ecosystem.