#cli
MCP explained in one drawing: how your AI gets inside your apps (Claude, n8n, Gmail) Here's how your AI actually gets inside your apps. It's called MCP, and it fits in one drawing. On its own, an AI is a brain in a box. It can talk and think, but it can't open your email or build anything in n8n. It has no hands. 1. The door is the API. Most apps have a door for other software: Gmail has one, GitHub has one, n8n has one. Every door is a different shape, with its own rules and its own key. 2. The plug is MCP. It's one standard shape. On one side is the AI. On the other side is a small program called an MCP server, one per app, and it knows that app's door. The AI plugs in, and the server does the walking through the door. 3. The menu is the list of tools. When the AI plugs in, it sees every tool the app offers, in plain words. Gmail's server offers create a draft, search mail and read a message. n8n's server offers list workflows, create a workflow and test it. The AI reads the list like a menu, picks a tool and calls it. That's how Claude builds a whole workflow inside n8n, node by node, and checks its own work, while you never open n8n. 4. Connecting one takes one sentence. In Claude Code, say: "Connect yourself to my n8n, here's the address and a key I made just for you." Claude writes a small settings file with the server's name and the key. Type /mcp and it says connected. That's the setup for most apps. Some, like Gmail, you just sign in to instead. 5. The key is the important part. An MCP server can only use the tools on its menu, and only as far as its key allows. So make a key that can do the job and nothing more. If the app lets you limit a key, make it read only when reading is all you need. If it doesn't, use a test account. And if a key ever leaks, cancel it inside the app. One click, and nobody can use it, the AI included. One honest line: MCP doesn't make the AI smarter. It gives a smart thing a way to act, and everything it does through that plug, it does as you. So you still check the work, like you would a new hire's. If you're starting from scratch, I have step-by-step lessons for all of this inside my community. There are eight courses, in order, from the basics of AI to automations, building websites and apps, and AI agents. If you're interested, the link is in my profile. #mcp #cli ##aiagents #aiautomation #claudecode
Professor Glitch18,500 views • 26 days ago
# Three doors, one building: API, CLI, MCP API, CLI and MCP are three ways to connect an AI system to a tool. Picture one building with three entrances. 1. **API: the loading dock.** A program sends a precisely formatted request and receives structured data. Useful for bulk work, repeatable integrations and precise operations. Store private credentials in the connection settings, and test generated code. 2. **CLI: the staff entrance.** The command-line interface exposes commands a program or AI coding tool can run. When a CLI supports your task, the AI can read its help and use the documented commands within your account permissions. 3. **MCP: the front desk.** The server exposes a menu of tools an AI application can discover and call. Some connections use a simple sign-in; others need setup. Server and account permissions determine what is actually available. For a supported everyday task, start with a trusted MCP connection. Inside Claude Code, a supported CLI can be convenient. For scale or a custom integration, check whether the API exposes the operation you need. These routes can overlap: a CLI or MCP server often calls an API underneath. My Workspace employee reads email and fills sheets through the command line. My Stripe MCP connection is configured read only, so it can inspect payment data without moving money through that connection. #api #cli #mcp
Professor Glitch22,500 views • 1 month ago
CLI, API, MCP — the 3 ways your AI connects to everything (and when to use each) Your AI's brain is useless if it can't reach anything — the real power is in the connections. There are exactly 3 doors your AI can use, and once you know all three you can connect it to basically anything: DOOR 1 — CLI (the workshop) → typed commands. Commands are text, and text is what AI does best — so an AI with terminal access is a power user at your machine. And it's not just local files: GitHub, Stripe, Google Cloud, even your whole Google Workspace ship command-line tools. You say "pull last month's payments" — it types the commands. Job's on your computer or a tool has a CLI → this door. DOOR 2 — API (the service counter) → every serious online service has an official software entrance. Send a precise request, get an exact structured answer. Trade-off: each service needs its own wiring + key. Need ONE service with deep control → this door. DOOR 3 — MCP (the universal plug) → the standard built FOR AI. A service runs a small MCP server that announces its tools, and any AI can plug in — no custom wiring. Plug in once, the tools just show up. Want plug-and-play → this door. The real answer: a serious AI employee uses all three. They're not competitors — they're three doors on the same building, and you pick per job. Want to learn this whole world from scratch — AI, automations, agents, connecting everything, all the way to AI employees? That's exactly what I teach. Link in my profile. #aiagents #cli #mcp #api
Professor Glitch12,200 views • 3 months ago
Let's --YOLO! Now in #GitHubCopilot #CLI!!! LET'S GO!!!!!!!!!
James Montemagno20,085 views • 10 months ago
What is the difference between CLI and MCP #cli #mcp #aiagent
Professor Glitch10,000 views • 5 months ago
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