A practical guide series on the Model Context Protocol - the open standard that lets Claude, LangGraph, n8n, and other AI apps connect to your actual tools and data instead of just guessing. Written by people who build agents for a living.
MCP in one picture: a host app talks to a server through a client, and the server exposes what it can do as tools, resources, and prompts.
Heard "MCP" everywhere and not sure what it actually does? These two guides get you oriented.
The plain-English version: the problem MCP solves, why it exists, and why it's often compared to a USB-C port for AI apps.
→The three pieces every MCP setup is built from, and how a single host can juggle several servers at once.
The vocabulary and the hands-on setup - what MCP servers offer, and how to actually connect one.
The three things a server can offer a model - what each one is for, and how a model actually decides to use them.
→A hands-on walkthrough - config files, stdio vs. remote transports, and getting your first server talking to Claude.
APA Mastery runs live, practical sessions on working with modern AI tools - not just theory.
See What's On →From connecting someone else's server to shipping your own.
Wrapping an existing API or database as an MCP server, and the security decisions that actually matter once other people can call it.
→How to navigate the public server directory, and what to check before trusting a third-party server with your data and credentials.
→Using the MCP Inspector, common failure modes, and how to verify tool-selection quality before a server ships.
→Prompt injection through tool output, scoping OAuth tokens correctly, and the confused deputy problem specific to agentic tool use.
→Letting a server call back into the model instead of only being called by it - and why it's used sparingly.
The host/client/server architecture, the three primitives, and the transport comparison, as one printable PDF. Drop your email and it's yours, plus a heads-up whenever new guides go live.
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