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14. Model Context Protocol (MCP)

Overview

The Model Context Protocol (MCP) is an open standard created by Anthropic that standardizes how AI applications connect to external tools, data sources, and services. Think of it as the USB-C of AI integrations — a universal interface that lets any compliant AI application (Cursor, Claude Desktop, Windsurf, your own agents) connect to any MCP server without custom integration code.

Lesson Map

# Lesson Focus
1 Why MCP The problem MCP solves — eliminating redundant integrations
2 How LLMs Use Tools Foundation — how tool calling works under the hood
3 Essentials of the Protocol The full MCP interaction flow — initialization, tool discovery, execution
4 MCP Architecture Core components — hosts, clients, servers, and their relationships
5 MCP Servers Server capabilities — tools, resources, prompts, sampling
6 LangChain MCP Adapter Bridging MCP tools into LangChain/LangGraph agents
7 MCP Quiz Knowledge check — 9 questions covering the full MCP stack

Architecture at a Glance

flowchart LR
    subgraph Host["🖥️ AI Application (Host)"]
        direction TB
        LLM["🤖 LLM"]
        C1["MCP Client 1"]
        C2["MCP Client 2"]
    end

    C1 <-->|"MCP Protocol"| S1["⚙️ MCP Server\n(Weather)"]
    C2 <-->|"MCP Protocol"| S2["⚙️ MCP Server\n(Stripe)"]

    S1 --> T1["🌤️ Weather API"]
    S2 --> T2["💳 Stripe API"]

    User["👤 User"] --> Host
    LLM <--> C1
    LLM <--> C2

    style Host fill:#1e3a5f,color:#fff
    style S1 fill:#10b981,color:#fff
    style S2 fill:#8b5cf6,color:#fff