Introduction
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Large Language Models are powerful reasoning engines, but they need clearly defined interfaces to interact with the real world effectively. In this lesson, you will move beyond the high-level concepts and get your hands dirty building the three fundamental components of any MCP server: Tools, Resources, and Prompts.
You will learn that Tools act as the “hands” of the model, enabling it to perform calculations and actions. You will discover how Resources act as the “eyes,” providing the necessary context and data. Finally, you will see how Prompts serve as the user interface, streamlining complex interactions into simple templates.
By the end of this lesson, you will be able to:
- Differentiate between the roles of Tools, Resources, and Prompts within the MCP architecture.
- Develop a functional MCP server that exposes active tools, static and dynamic resources, and user-facing prompts.
- Validate your server capabilities using the MCP Inspector, a powerful web-based tool for testing without a full client interface.
These skills are the foundation of building robust AI agents. Instead of just “chatting” with an AI, you will learn how to engineer the specific capabilities it needs to work for you.