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What is MCP?

The Model Context Protocol is an open standard that lets AI models use your product — call its functions, read its data — through one common language instead of a custom integration per AI.

AI client
Claude, IDEs, agents
MCP server
your tools, hosted
Your API
the product you have
tools/call →
← result
HTTPS →
← JSON

The USB-C moment for AI

Before USB-C, every device shipped its own charger. Before MCP, every AI integration was its own charger: connecting one assistant to one product meant custom code, custom auth, custom maintenance — and doing it all again for the next assistant.

MCP (Model Context Protocol) replaces that with a single, open standard. Your product exposes an MCP server; any AI that speaks the protocol — Claude, AI-powered IDEs, autonomous agents, or a chat widget inside your own product — can discover what your server offers and use it, safely and with permission.

What an MCP server actually exposes

Tools are functions the AI can call — invoices.search, orders.refund — each with a typed description that tells the model when and how to use it. The AI asks; your server executes; the result comes back as structured data the model can reason about.

Resources are things the AI can read — documents, records, knowledge — so answers come from your actual data instead of the model’s memory. Together they turn an AI from “something that talks about your product” into “something that operates your product.”

The part everyone underestimates: identity

The protocol defines how an AI calls a tool. Production reality asks harder questions: as whom? With what permissions? Rate-limited how? Logged where? A well-built MCP server authenticates every call as a specific user, scopes it to what that user may do, and keeps an audit trail. That’s the difference between a demo and something you can put in front of customers — and it’s exactly the layer CMD+K’s hosted gateway handles for you.

Where you meet MCP in the wild

A customer connects your product to Claude and asks it to pull this quarter’s numbers. A developer’s IDE queries your API docs mid-refactor. A support assistant inside your own app resends an invoice on request. Different surfaces, one protocol underneath — which is why teams that publish an MCP server once keep finding new places it plugs in. Browse real connector examples in the marketplace, or see how a team ships one in the use cases.

Ship the layer between
your product and AI.

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