Model Context Protocol (MCP): Hands-On with Agentic AI
30mGeneral2025-03-24
Authors
Morten Rand-Hendriksen
Senior Staff Instructor, Speaker, Web Designer, and Software Developer
Course details
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.
Learning objectives
Define and understand Model Context Protocol (MCP).
Discover available MCP servers.
Install and use MCP servers in Claude Desktop.
Install and use MCP servers in Cursor.
Build custom MCP servers in Python and Typescript.
Learning objectives
Define and understand Model Context Protocol (MCP).
Discover available MCP servers.
Install and use MCP servers in Claude Desktop.
Install and use MCP servers in Cursor.
Build custom MCP servers in Python and Typescript.
Skills covered
ClaudeAnthropicAPIsAI Productivity ToolsGenerative AIArtificial Intelligence for BusinessArtificial Intelligence (AI)Business Software and ToolsSoftware DevelopmentOne-Off
Concepts
Introduction
- MCP - Connecting AI agents to data, apps, and more
MCP Explained
- Using MCP servers in Claude Desktop
- Model Context Protocol (MCP) explained
- Exploring avaialble MCP servers and clients
- Limiting the blast radius of AI agents
- Leveraging the power of MCP servers
- Using MCP servers in Cursor
Building MCP Servers
- Building your own MCP servers
- Testing with the MCP inspector
- Troubleshooting MCP servers
Conclusion
- Building AI agents with MCP