Introduction to Model Context Protocol

Model Context Protocol: The Universal Adapter

The Model Context Protocol (MCP) is an open standard that defines how AI agents communicate with tools, data sources, and other services. Think of it as USB-C for AI - a universal interface.

The Problem MCP Solves

Before MCP, every AI application had to:

Write custom integrations for each tool
Define proprietary schemas for context passing
Handle authentication differently for each service
Reinvent context management from scratch

MCP standardizes all of this, so you write once and connect to any MCP-compliant tool.

MCP Architecture

Core MCP Concepts

Concept	What It Does	Example
Resources	Data the agent can read	Files, database rows, API responses
Tools	Actions the agent can take	Send email, query database, create file
Prompts	Reusable prompt templates	Summarization prompts, analysis prompts
Sampling	LLM completion requests	Ask the model to generate text

Why MCP Matters for Production

Interoperability: Any MCP client works with any MCP server
Security: Standardized permission model
Observability: Consistent logging and tracing
Ecosystem: Growing library of pre-built connectors