DeepLearning.AI

Elie Schoppik

In this course, you will explore the Model Context Protocol (MCP) and its role in standardizing AI application development. Learn to build and deploy MCP servers, create MCP-compatible applications, and connect AI applications to external systems. By the end, you'll be equipped to develop AI applications with rich context and minimal integration work.

Build Rich-Context AI Apps with Anthropic

An overview of the course and its objectives.

Introduction

Understanding the need for MCP in AI development and its benefits.

Why MCP

Exploring the client-server architecture of MCP and its communication mechanisms.

MCP Architecture

Building a chatbot with custom tools and making it MCP-compatible.

Chatbot Example

Steps to build and deploy an MCP server using FastMCP.

Creating an MCP Server

Developing an MCP client to connect to the server dynamically.

Creating an MCP Client

Integrating the chatbot with reference servers for enhanced functionality.

Connecting the MCP Chatbot to Reference Servers

Incorporating additional features into the MCP server.

Adding Prompt and Resource Features

Setting up servers to work with Claude Desktop.

Configuring Servers for Claude Desktop

Deploying MCP servers remotely and testing them with MCP Inspector.

Creating and Deploying Remote Servers

Summarizing the course content and key takeaways.

Conclusion

A short quiz to test your understanding of the course material.

Quiz

Additional resources and tips for successful MCP implementation.

Appendix – Tips and Help

Join this short course to learn how to build rich-context AI applications using the Model Context Protocol (MCP). Gain hands-on experience in integrating AI applications with external systems, simplifying development, and reducing fragmentation.

Developers looking to integrate rich context into AI applications using standardized protocols.

AI Developers

Teams aiming to streamline AI development and reduce fragmentation across projects.

Technical Teams

Individuals interested in learning about the latest advancements in AI application development.

AI Enthusiasts

Artificial Intelligence

Business

Cloud Engineering

Cybersecurity

Data

Design

Devops

Finance

Green Skills

Languages

AI Foundations

AI for Business

AI Automation & Workflows

Agentic AI

AI Coding / Vibe Coding

Agile and Scrum Methodologies

Agile and Scrum Practices 

AI Automation & Orchestration

AI for Data

AI for Design

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Build Rich-Context AI Apps with Anthropic

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