If you follow AI news at all, you've probably seen the acronym "MCP" floating around. Maybe in a LinkedIn post. Maybe in a headline you skimmed past because it sounded like another technical buzzword that doesn't apply to your business.
It does apply to your business. Here's why.
MCP in plain English
MCP stands for Model Context Protocol. That's a mouthful, so let's skip straight to what it actually means.
Right now, AI tools like ChatGPT and Claude are incredibly capable, but they live in a bubble. They can write, analyze, brainstorm, and answer questions all day long, but they can't see your actual business data. They don't know what's happening in your Google Analytics. They can't pull up your search rankings. They can't check your CRM or read your project management board.
MCP changes that. It's a standard way to connect AI tools directly to external systems (your analytics, your databases, your business tools) so the AI can work with your real data instead of just guessing.
Think of it like this: without MCP, asking an AI about your website traffic is like hiring a consultant and never giving them access to any of your numbers. With MCP, you hand them the keys to the dashboard.
Why should a business owner care?
Because the gap between "AI that talks about your data" and "AI that works with your data" is enormous.
Here's a practical example. Say you want to know why your website traffic dropped last week. Without MCP, you'd log into Google Analytics, dig through reports, switch over to Search Console, run some queries, compare date ranges, maybe export a spreadsheet, and try to piece together what happened. That's an hour of your day, minimum.
With MCP connected to both Google Analytics and Search Console, you can just ask: "My organic traffic dropped last week. What happened?"
The AI checks both data sources, cross-references the numbers, and gives you an answer. In plain English. In seconds.
That's not a hypothetical. That's something you can set up right now. We wrote a step-by-step guide to connecting Google Analytics and Search Console to Claude Code if you want to see exactly how it works.
What "connected AI" actually looks like
Once your analytics tools are connected through MCP, the kinds of questions you can ask in plain English include:
- How many users visited my site in the last 30 days?
- What are my top landing pages by sessions this month?
- Which search queries are driving the most clicks?
- Where do I rank between positions 5 and 15? (These are your quick-win SEO opportunities.)
- Which pages get a lot of search impressions but low click-through rates?
No dashboards. No exports. No switching between three different tabs. Just a question and an answer.
The real power is combining data sources. You can ask something like "find pages where search impressions are growing but on-site engagement is low." That kind of cross-referencing used to require an analyst or a lot of patience with spreadsheets. Now it takes a sentence.
It's not just analytics
Google Analytics and Search Console are a great starting point, but MCP servers already exist for a long list of tools. Slack, GitHub, Salesforce, PostgreSQL databases, Google Drive, file systems. The list keeps growing.
Anthropic (the company behind Claude) created the protocol and open-sourced it in late 2024. Since then, Google, OpenAI, Microsoft, and hundreds of independent developers have adopted it. It's quickly becoming the standard way AI tools connect to everything else.
For business owners, that means the list of things AI can actually help with is expanding fast. And the barrier to connecting your tools keeps getting lower.
What this doesn't mean
A few things worth clarifying, because there's a lot of hype out there.
MCP connections are read-only by default. When you connect your analytics, the AI can query your data but can't change settings, delete anything, or modify your configuration. Your data stays safe.
MCP also isn't a product you buy. It's an open standard, like USB or Bluetooth, but for AI connections. You don't pay for MCP itself. You just set up the connections between the tools you already use and the AI tools you already have access to.
And you don't need to be technical to benefit from it. Setting up the connections does involve some terminal commands (or you can have someone do it for you), but once it's configured, you're just asking questions in plain English.
Where this is headed
There's a pattern we see with small businesses and AI adoption. Most people start with the basics: writing assistance, meeting notes, maybe some light automation. That's real value, and it's a smart place to begin.
But the next level is when AI connects to your actual systems. When it can answer questions about your business using your data, not generic advice. When you can automate workflows that used to require switching between five different tools and a spreadsheet.
MCP is the infrastructure that makes that possible. And it's available today.
Getting started
If you want to try this yourself, the easiest entry point is connecting your Google Analytics and Search Console to Claude Code. It's a one-time setup that takes about 30 minutes, and once it's done, you have an AI-powered analytics assistant available in every project.
We put together a detailed walkthrough with every step, including the Google Cloud setup, server installation, and troubleshooting. It's written for people who are comfortable copying and pasting terminal commands. No deep technical knowledge required.
If you'd rather not set it up yourself, or you're curious about connecting AI to other parts of your business (your CRM, your project management tools, your internal databases), that's exactly the kind of thing we help with. We'll figure out what's worth connecting and set it up properly, so you can focus on running your business.