English | MP4 | AVC 1920×1080 | AAC 44KHz 2ch | 96 Lessons (6h 36m) | 6.64 GB
Step-by-step guide to AI agents with MCP: build servers, integrate APIs, and unlock real AI applications
Be ahead of the curve and build Real AI Agents with Model Context Protocol (MCP)
AI is powerful — but on its own, it’s limited. Without access to tools, APIs, and real-world data, AI agents can’t do much beyond generating text.
That’s where Model Context Protocol (MCP) comes in. MCP is the new standard for giving AI real capabilities: connecting models to APIs, databases, and even your own computer.
In this hands-on course, you’ll learn step by step how to build, deploy, and integrate your own MCP servers — turning AI into something that actually does things.
Why This Course Over Others?
Most resources on MCP are either incomplete or highly technical without context.
This course is different because it is:
- Project-based — you’ll build real servers, not just read theory
- Up-to-date — covering the latest MCP standard as it evolves
- Practical — you’ll connect MCP to tools you already use (APIs, email, calendar, databases)
- Proven teaching style — trusted by over 500,000 learners worldwide
- Supported — with Q&A help and future updates as MCP grows
If you want the most practical, hands-on, and beginner-friendly path into MCP, this is the course.
Why Learn MCP?
MCP is quickly becoming the backbone of next-generation AI. Early adopters are already using it to:
- Automate workflows with custom AI assistants
- Connect AI to APIs, calendars, and emails
- Fetch and process real-world data in real time
- Build integrations that save time and money
By learning MCP now, you’ll be ahead of the curve — with skills companies and clients are actively searching for.
What You’ll Learn
By the end of this course, you’ll:
- Understand MCP servers deeply — from core concepts to deployment
- Build your own server with guided, hands-on projects
- Integrate AI with APIs, databases, and external tools
- Unlock real-world AI applications that go beyond simple chat
How You’ll Learn
This course is fully project-based. You’ll:
- Follow along with real, working examples
- Get downloadable code and templates
- Reinforce your skills through guided exercises
- Build tools you can actually use in your own work
Who This Course Is For
- Developers who want to add cutting-edge AI skills
- Tech professionals who need to connect AI to real-world systems
- Freelancers and entrepreneurs who want to automate and scale tasks
- Anyone who wants to stay ahead as AI reshapes every industry
Table of Contents
Get Started with the course AI Agents & MCP
1 Introduction
2 What You Will Learn
3 Requirements
4 Course Structure
Building AI Agents Step by Step
5 Introduction to Agents
6 What is an Agent
7 ReAct Prompting
8 Tool Calling
9 Agent Demo
Mastering Model Context Protocol (MCP)
10 Introduction to MCP
11 Resources
12 MCP Overview
13 Common MCP Clients
14 Common MCP Servers
15 [IMPORTANT] Fix MCP Support on VS Code
16 Install MCP Servers
17 Environment Setup
18 Create a simple MCP Server
19 Debug Your MCP Server
20 Install Your MCP Server
APIs for AI Developers — Foundations & Hands-On
21 Introduction
22 Resources
23 What is an API
24 Awesome APIs
25 Bruno API Clients
26 HTTP Methods
27 Notebook Experiment with an API
28 Conclusion
29 Challenge
Create a News MCP Server
30 Introduction
31 Resources
32 Materials We Will Use
33 Environment Setup
34 Create Your MCP Server With LLMs
35 Code Review
36 Debug with MCP Inspector
37 Try It Out
38 Challenge
MCP Transports — How Agents Communicate
39 Introduction to Transports
40 Client-Server Architecture
41 JSON-RPC Messages
42 Transports in MCP
MCP Security — Protecting Your AI Systems
43 Introduction
44 Resources
45 Malicious MCP Servers
46 Create a Malicious MCP Server
Remote MCP Servers — Scaling AI Beyond Local
47 Introduction to Remote MCP
48 Resources
49 Streamable HTTP
50 Create a Remote MCP Server
51 Connect to a Remote MCP Server
52 MCP on FastAPI
53 Multiple MCP Servers on a Single App
MCP Authentication — Securing Access
54 Introduction to Authentication
55 Resources
56 The Need for Auth in MCP
57 Why not Local Auth in MCP
58 Shift to Remote MCP
59 What is OAuth
60 OAuth 2.1 Workflow
61 Starting point MCP Without Auth
62 ScaleKit Auth Stack
63 Endpoint Discovery
64 Create Auth Middleware
65 Token Validation
66 Auth In Action
Agentic RAG with MCP
67 Intro
68 Resources
69 What is RAG
70 RAG Pipeline
71 Embeddings
72 Vector Databases
73 Agentic RAG
74 Notebook Setup
75 Notebook Extraction
76 Notebook Loading
77 Notebook Query the Database
78 MCP Server Set Up Environment
79 MCP Server Initialize Database
80 MCP Server Ingest Documents Tool
81 MCP Server Initialize Server & Tools
82 MCP Server Debugging
83 MCP Server Create Query DB Tool
84 MCP Server Create Status Tool
85 MCP Server Test it on Remote Client!
Final Project Deploy Your MCP Server
86 Introduction
87 Resources
88 Render
89 Turn MCP Server into Remote MCP Server
90 Add Auth to MCP Server
91 Register on Scalekit
92 Push to GitHub
93 Deploy to Render
94 Update ScaleKit Prod Config
95 Demo of Deployment
Conclusion
96 End
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