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home/pathways/mcp-model-context-protocol
IntermediateLearning Pathway

MCP: Model Context Protocol

Master the open protocol that connects AI agents to every tool, API, and data source — from building your first MCP server to securing multi-agent deployments in enterprise.

12articles
~6htotal
Intermediate
Start Pathway →All Pathways

What you'll learn

  • MCP architecture: primitives, transports, capabilities, and the full security model
  • Build a working TypeScript MCP server with tools, resources, and Claude Code wiring
  • MCP security: prompt injection, confused deputy attacks, OAuth patterns, audit logging
  • When to use RAG vs MCP for different context-augmentation scenarios
  • Enterprise MCP: managed auth with Okta, Claude for Enterprise, and SSO

Frequently asked questions

What is MCP (Model Context Protocol)?+

MCP is an open protocol, developed by Anthropic and adopted across the industry, that standardizes how AI agents connect to external tools, data sources, and APIs. Instead of building custom integrations for each AI tool, MCP provides a standard interface: an MCP server exposes tools and resources; an MCP client (like Claude Code or Claude Desktop) connects to them. This pathway covers the full protocol — architecture, security, and implementation.

Is MCP only for Claude?+

MCP was created by Anthropic and is natively supported by Claude products, but the protocol is open and has been adopted by other AI tools and frameworks. The implementation skills you learn — building MCP servers, handling authentication, managing tool schemas — transfer across any MCP-compatible client.

How long does the MCP pathway take?+

11 articles, approximately 6 hours. The pathway progresses from understanding the protocol to building your first server to securing production deployments — each stage builds on the last.

Continue learning

AI Foundations

B

Understand what AI actually is — tokens, transformers, agents, and the landscape. Start here if you're new.

11 articles · ~4h →

Prompt Engineering

B

Go from vague requests to precise, reproducible AI outputs. The skill that underpins everything.

13 articles · ~5h →

Claude Code Mastery

I

Go from zero to productive with Claude Code — the terminal AI coding agent that ships real projects.

15 articles · ~7h →
Sandbox patterns for isolating agent context across MCP sessions

Curriculum — 12 articles

01

What Is MCP? Model Context Protocol Explained

Architecture, primitives, transports, security, and ecosystem — the complete guide.

18m→
02

Build Your First MCP Server: Step-by-Step Guide

Working TypeScript MCP server with tools, resources, and Claude Code wiring.

14m→
03

MCP Tool Descriptions: Write for Reliable Agent Selection

Why minimal descriptions cause misrouting and how to write descriptions that prevent selection failures in production.

12m→
04

MCP Security: Threats, Auth, and Safe Deployment

Prompt injection, confused deputy, OAuth patterns, audit logging — the full security guide.

18m→
05

RAG vs MCP: Complete Guide to Context-Aware AI

When to use retrieval augmentation vs structured tool access.

10m→
06

How to Use Claude Connectors & MCP Servers

End-to-end guide to wiring Claude up with connectors and MCP.

10m→
07

Claude Code MCP Servers: Connect Any Tool to Your Agent

Extend Claude Code with databases, APIs, and external tools.

10m→
08

Top 10 MCP Server Directories in 2026

Where to find, publish, and discover MCP servers.

8m→
09

OpenAI Secure MCP Tunnel Guide

How OpenAI exposes tools over MCP — and what it means for security.

8m→
10

Claude Enterprise + MCP + Okta: Managed Auth in Production

SSO, managed auth, and MCP security for enterprise deployments.

8m→
11

Context Mode: MCP Sandboxing for Agent Context

Isolate agent context with MCP sandbox patterns.

8m→
12

OpenCut: Plugins and Headless MCP in Practice

How OpenCut used MCP to build a headless plugin system.

8m→

Start learning

MCP: Model Context Protocol

Articles12
Time commitment~6h
LevelIntermediate
AccessFree
Start Pathway →

Free account. No credit card needed.

Who this is for

  • →Developers building or integrating MCP servers
  • →Platform engineers connecting AI agents to internal tools and APIs
  • →Security engineers evaluating MCP deployment risk
  • →Teams standardizing on MCP for their AI tooling layer

After this pathway

Build, secure, and deploy MCP servers that reliably extend Claude and other AI agents with your organization's tools, data, and APIs.

Building AI Agents

I

Understand and build the loops, harnesses, and protocols that make AI agents reliable and autonomous.

16 articles · ~6h →

AI Tools by Role

B

Practical AI adoption for your specific function — marketing, engineering, HR, finance, and more.

10 articles · ~4h →

AI Model Landscape

I

Navigate the crowded model market — Claude, GPT, Gemini, open-source — and understand the tradeoffs.

13 articles · ~6h →