# Introduction to Model Context Protocol (MCP)
In today's rapidly evolving landscape of Large Language Models (LLMs), the ability for these powerful AI applications to interact seamlessly with external systems, tools, and data sources is paramount. Whether it's fetching real-time information, executing actions, or integrating with existing enterprise systems, a robust communication framework is essential.
This module introduces the **Model Context Protocol (MCP)**, a standardized protocol designed precisely for this purpose. MCP provides a flexible and extensible architecture that enables LLM applications (referred to as **Hosts**) to communicate effectively with various **integrations** (represented by **Servers**) through dedicated **Clients**.
By the end of this module, you will:
* Understand the fundamental purpose and necessity of MCP in the LLM ecosystem.
* Grasp the core client-server architecture, distinguishing between Hosts, Clients, and Servers.
* Identify the key communication layers, including the **Protocol layer** (handling message framing and high-level patterns) and the **Transport layer** (managing the actual data exchange, often via JSON-RPC over Stdio or HTTP with SSE).
* Recognize the basic message types (requests, results, errors, notifications) and the typical connection lifecycle (initialization, message exchange, termination).
This module serves as your foundational step in the "Getting Started with Model Context Protocol (MCP)" course, laying the groundwork for understanding how LLM applications can unlock their full potential through powerful and secure external integrations. Let's dive in and explore the architecture that makes intelligent LLM interactions possible.
