Glossary

What is MCP (Model Context Protocol)?

The Brimm team · grounded in the docs

MCP, the Model Context Protocol, is an open standard that Anthropic released in November 2024 for connecting AI applications to external systems: data sources, tools, and services. The official protocol site explains it with an analogy: “Think of MCP like a USB-C port for AI applications.” One standard plug instead of a custom integration per pairing. It is not a search engine and not a ranking system. It matters to site owners for a narrower reason: it is part of the plumbing that lets AI assistants act on the web, not just read it.

The short definition

Before MCP, every AI product that wanted to reach your database, your calendar, or your API needed a bespoke integration, and every tool vendor needed one per AI product. MCP replaces that grid of one-off connectors with a single protocol. The spec site defines it as an open-source standard for connecting AI applications to external systems, and describes the payoff plainly: using MCP, AI applications like Claude or ChatGPT can connect to data sources, tools, and workflows, letting them access key information and perform tasks. A developer builds one MCP server for their service, and any MCP-capable assistant can use it. Anthropic created the protocol; it is now open and supported across clients from multiple companies, including Claude, ChatGPT, and development tools like VS Code and Cursor.

How it works, briefly

Three roles. An MCP host is the AI application the person is talking to. It runs an MCP client that speaks the protocol. An MCP server is the thing being connected to, exposing three kinds of capability: tools the model can call, resources it can read, and prompts it can reuse. When you hear that an assistant "has access to" a booking system or a product catalog, increasingly this is the mechanism underneath. The details live in the spec at modelcontextprotocol.io and are aimed at developers. You do not need them to run a business website. You need the paragraph below.

Why site owners will care

Assistants are moving from answering questions to completing tasks: find a plumber, compare three quotes, book the appointment. That shift is called agentic search, and MCP is one of the standards making it practical, because it gives agents a uniform way to reach services. The consequence for a website is blunt. An agent visiting your site is a machine reader with a goal. It does not admire your hero animation. It needs your hours, prices, service area, and booking path in a form it can parse and act on. Sites that are legible to machines get chosen by agents; sites that render everything in JavaScript and bury facts in images get skipped for a competitor that answered cleanly. The groundwork is the same work AI citation already demands: real HTML, structured data, specific facts stated in text.

The honest scope

We will not sell you an MCP SEO angle, because there is not one. MCP is a tool-connection protocol, not a discovery or ranking system. There is no MCP markup to add to a webpage, no MCP file that makes Google or ChatGPT prefer you, and anyone offering "MCP optimization" for an ordinary business site is dressing up folklore. Where it becomes real for most businesses is indirect: the platforms you already use, booking systems, commerce platforms, review services, are wiring themselves into assistants over MCP, and your data rides along. Building your own MCP server only makes sense when you have a service developers or agents should call programmatically. For everyone else, the practical move is agent readiness on the website itself, which is measurable today.

What to do about it

Treat MCP as a signal of where the traffic is going, not a task on your list. The tasks are the ones that make any machine reader succeed: keep content in raw HTML, state facts as text, mark up your identity and offerings with schema, and let the crawlers in. That is what we measure. Run your site through Brimm to see how it reads to a machine with a goal, or start with the background in what is generative engine optimization (GEO) and why isn't my site in AI search.