MCP Crash Course: Build a Conversational Multi-Agent System | Udemy [Update 06/2025]
English | Size: 0.97 GB
Genre: eLearning[/center]

Create intelligent LLM agents that interact with tools, databases, and users using the MCP protocol.

What you'll learn
Learn how to build intelligent agents that use LLMs to make decisions and perform actions in real time
Use the MCP protocol to integrate language models with tools, data, and external systems
Create custom Tools that LLMs can use to interact with their environment
Develop MCP servers and clients capable of asynchronous and efficient communication
Build conversational interfaces with Streamlit connected to LLM-based agents
Learn through practical examples how to build, test, and expand your own connected LLM agents

Welcome to the MCP Crash Course, your fast track to building real, intelligent multi-agent systems powered by Large Language Models (LLMs) and the Model Context Protocol (MCP).

If you've ever wanted to go beyond simple chatbots and create agents that can think, act, and interact with the world around them, this course is for you.

What You'll Build

In this hands-on course, you'll design and implement a complete conversational multi-agent system using MCP - from setup to deployment. By the end, you'll have built an intelligent chatbot that doesn't just reply - it retrieves data, executes commands, accesses APIs, and interacts in structured, meaningful ways.

What You'll Learn

MCP Fundamentals - Understand how MCP structures communication between LLMs, clients, and servers
Agents Architecture - Learn how agents reason, make decisions, and call external tools
MCP Components - Deep dive into Tools, Resources, and Prompts, the core of every MCP integration
Building MCP Servers & Clients (Python SDK) - Create and connect real servers and clients using Python
Streamlit Interfaces - Build a conversational front-end for your agent
Integrations - Combine MCP with LangChain, Docker, and real API connections
Security & Deployment - Learn best practices for containerization, authentication (OAuth 2.0), and production setups

Why MCP

MCP (Model Context Protocol) is quickly becoming the standard for building intelligent, secure, and extensible AI systems. It's the technology adopted by Anthropic, OpenAI and Microsoft - among others - to make LLMs truly interactive and tool-aware. Once you master MCP, you can build agents that act, not just chat.

Course Highlights

100% hands-on, project-based learning

Build multiple MCP clients and servers from scratch

Step-by-step instruction with practical examples

Ideal for developers exploring GenAI integrations and multi-agent architectures

Full access to code, notebooks, and implementation guides

Who This Course Is For

AI Engineers and Developers

Data Scientists building intelligent systems

GenAI users who want to connect LLMs to real-world data and actions

Backend Developers interested in learning how to make LLMs interact with services, APIs, and local systems

Automation Engineers seeking to orchestrate intelligent processes using AI agents and MCP

Researchers and Students exploring the next generation of AI architectures and agent frameworks

Python Developers who want to apply their Python knowledge to real-world AI systems

Tech Enthusiasts curious about building practical AI tools instead of just using pre-built chatbots

Startups and Innovators aiming to prototype or deploy AI-powered assistants and workflows

By the end of the course, you'll know exactly how to build, deploy, and expand your own MCP-based conversational agent system, the kind of architecture powering the next generation of AI applications.

Who this course is for:
For anyone interested in learning how to build agents with MCP in practice.

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