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This is a code repository for the LinkedIn Learning course Model Context Protocol (MCP): Hands-On with Agentic AI [ASI] [TEXT] [MODELS]

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Model Context Protocol (MCP): Hands-On with Agentic AI

This is the repository for the LinkedIn Learning course Model Context Protocol (MCP): Hands-On with Agentic AI. The full course is available from LinkedIn Learning.

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Course Description

The Model Context Protocol (MCP) allows developers to add agent behavior to LLMs by providing a universal protocol providing context to language models so they can interface with data and applications in a consistent way. MCP servers expose resources (data), tools (actions), and prompts (instructions) for the LLM and the user to use in performing more complex operations. In this course you’ll explore how the MCP works in Claude Desktop to extend its functionality, and you’ll build your own MCP servers using Python and TypeScript to give LLMs new capabilities to do things on the computer, connect with external APIs, and perform advanced multi-step actions.

Instructions

You can work with these files in GitHub Codespaces or in an editor on your computer.

To run the MCP servers in development mode using the MCP Inspector and test them in Claude Desktop and Cursor, you need to clone the repository to your computer.

Contents

This repository contains folders with supporting files for the course.

Example MCP Servers

Hands-on Practice

  • gh-models-helper: Starting point for "Building an advanced MCP server using TypeScript"

MCP Server Templates

Branches

This repository does not use branches.

Installing

Each folder has a README.md file with installation instructions.

Instructor

Morten Rand-Hendriksen

Principal Staff Instructor, Speaker, Web Designer, and Software Developer

Check out my other courses on LinkedIn Learning.

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This is a code repository for the LinkedIn Learning course Model Context Protocol (MCP): Hands-On with Agentic AI [ASI] [TEXT] [MODELS]

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