A platform team supports four AI applications and six internal systems. Every application that needs a system has its own connector, and every new system means writing four more. What does adopting a shared protocol change about that arithmetic?

The principle — Bespoke integration cost grows with the product of the two populations. A shared protocol turns that product into a sum.

Why the key is correct — MCP is an open-source standard for connecting AI applications to external systems, and the documentation's own framing is that it provides a standardized way to connect them, in the way a common port does. Six systems each exposing one server, and four applications each speaking the protocol, is ten pieces of work rather than twenty-four — and the eleventh system costs one more, not four.

Why the others are wrong — Shorter connectors still leave you writing one per pair, which is the cost being removed. The systems still expose something; that something is now a server rather than a bespoke endpoint. And the arithmetic improves the moment both sides conform, without waiting for a vendor to dominate — the protocol is already supported across a wide range of clients and servers.

Remember this — The win is fewer integrations, not smaller ones.

Sources — MCP first-party documentation.