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Model Context Protocol | MCP | 2025
Rating: 4.1 out of 5(8 ratings)
347 students

Model Context Protocol | MCP | 2025

Understand the Theory behind MCP | Build MCP Servers with FastMCP & Deploy on Google Cloud
Created byJohannes Hayer
Last updated 7/2025
English

What you'll learn

  • Model Context Protocol (MCP) Architecture
  • Model Context Protocol (MCP) Transport
  • Model Context Protocol (MCP) Delievery
  • FastMCP Intro
  • Model Context Protocol (MCP) Tools - How to apply it with FastMCP
  • Model Context Protocol (MCP) Resources - How to apply it with FastMCP
  • Model Context Protocol (MCP) Prompts - How to apply it with FastMCP
  • Model Context Protocol (MCP) - How to deploy with Docker to Google Cloud

Course content

1 section • 13 lectures • 1h 45m total length

  • Resources0:01
  • Motivation5:46

    Explore how large language models gain value when given custom context and see MCP, a USB-C-like protocol, standardizing data-source connections via AMQP.

  • Architecture6:25
  • Transport7:40

    Explore the MCP transport layer and JSON RPC message types - requests, responses, and notifications - and how they travel via SDO, server sent events, or streamable http.

  • Discovery2:52
  • Theory Quiz
  • FastMCP Intro6:05

    Learn to build an MCP server with fast MCP in Python, using decorators to generate tool schemas, set up with uv, and test via the amqp inspector across protocols.

  • MCP Tools12:22
  • MCP Resources15:09

    Explain how resources in the MCP server become application controlled, including uris, dynamic resource templates, and client-driven selection to fetch system and customer logs.

  • MCP Prompts6:27

    Prompts are predefined AMQP prompt templates for AI interactions stored on the server, enabling users to generate customer issue summaries from logs with a client-side language model.

  • Deploy your MCP Server to Google Cloud20:17

    Deploy your MCP server to Google Cloud with Docker, push the image to Artifact Registry, and run on Google Run with proper tagging and HTTP transport.

  • Outro1:19

    Explore the model context protocol (MCP), its transport layer, and build a real MCP server with fast MCP, using the Technova example to integrate tools and prompts in lm apps.

  • The End? Some more Goodies2:47
  • Final Quiz
  • BONUS: Vibe code MCP Server18:20

Requirements

  • Basic programming skills
  • Basic Python skills
  • Basic Docker skills
  • Basic understanding of APIs and web services

Description

The AI industry just unified around ONE integration standard - and you need to know it.


In March 2025, OpenAI officially adopted MCP. Google DeepMind followed in April, calling it "rapidly becoming the open standard for the AI agentic era." Over 5,000 MCP servers now exist in the ecosystem, growing from zero in just 6 months.

This isn't just another protocol - it's the "USB-C for AI applications" that enterprises like Goldman Sachs, AT&T, and Block are already using in production.


The Problem MCP Solves

Before: "Who are our at-risk customers?" → "I don't have access to your CRM system..."
After: "Based on your Salesforce data, 5 enterprise customers are at risk this month: Acme Corp has 72% decreased usage, 3 open tickets, renewal in 45 days..."


What You'll Build

Create a Support Assistant:

  • MCP Server with FastMCP (Python)

  • Real-time log monitoring and customer data integration

  • AI-powered support summaries using live business data

  • Containerized deployment on Google Cloud with Docker


Why This Course Is Critical NOW

Industry Standard: OpenAI, Google, Microsoft Azure all support MCP
Explosive Growth: 5,000+ servers created in 6 months
Enterprise Adoption: AWS, Block, Apollo, GitHub using it in production
Developer Velocity: Zed, Replit, Sourcegraph building on MCP
Career Future-Proofing: Join the ecosystem before it becomes mandatory


What You'll Master

MCP Protocol Mastery: Architecture, transports
FastMCP Development: Tools, Resources, Prompts, and Sampling
Enterprise Integration: Real business data connections
Production Deployment: Docker, Google Cloud, monitoring

Don't get left behind. While others scramble to learn MCP when it becomes mandatory, you'll already be the expert building the next generation of AI-integrated applications.


Who this course is for:

  • Backend developers working on AI-powered applications
  • DevOps engineers deploying AI systems
  • Software architects designing AI integration strategies
  • Technical leads implementing enterprise AI solutions

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