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.
What Is MCP? Model Context Protocol Explained
Architecture, primitives, transports, security, and ecosystem — the complete guide.
Build Your First MCP Server: Step-by-Step Guide
Working TypeScript MCP server with tools, resources, and Claude Code wiring.
MCP Security: Threats, Auth, and Safe Deployment
Prompt injection, confused deputy, OAuth patterns, audit logging — the full security guide.
RAG vs MCP: Complete Guide to Context-Aware AI
When to use retrieval augmentation vs structured tool access.
How to Use Claude Connectors & MCP Servers
End-to-end guide to wiring Claude up with connectors and MCP.
Claude Code MCP Servers: Connect Any Tool to Your Agent
Extend Claude Code with databases, APIs, and external tools.
Top 10 MCP Server Directories in 2026
Where to find, publish, and discover MCP servers.
OpenAI Secure MCP Tunnel Guide
How OpenAI exposes tools over MCP — and what it means for security.
Claude Enterprise + MCP + Okta: Managed Auth in Production
SSO, managed auth, and MCP security for enterprise deployments.
Context Mode: MCP Sandboxing for Agent Context
Isolate agent context with MCP sandbox patterns.
OpenCut: Plugins and Headless MCP in Practice
How OpenCut used MCP to build a headless plugin system.
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.
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.
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.
Understand what AI actually is — tokens, transformers, agents, and the landscape. Start here if you're new.
10 articles · ~4h →Go from vague requests to precise, reproducible AI outputs. The skill that underpins everything.
11 articles · ~5h →Go from zero to productive with Claude Code — the terminal AI coding agent that ships real projects.
13 articles · ~7h →Understand and build the loops, harnesses, and protocols that make AI agents reliable and autonomous.
11 articles · ~6h →Practical AI adoption for your specific function — marketing, engineering, HR, finance, and more.
10 articles · ~4h →Navigate the crowded model market — Claude, GPT, Gemini, open-source — and understand the tradeoffs.
10 articles · ~6h →
