If you use AI tools like Claude, you've probably run into the letters MCP. It sounds technical, but the idea is simple. Here's what an MCP server is, what it's for, and when it makes sense for a small or mid-size business.
The idea in one sentence
MCP (Model Context Protocol) is an open standard that connects AI to your tools and data. It was introduced by Anthropic, the company behind Claude, and many other AI apps support it today.
An MCP server is the small program that acts as the bridge. It tells the AI "here's what you can look up or do here," and carries out the action when the AI asks.
An analogy
Think about the USB port on your laptop. Before USB, every printer, mouse and keyboard needed its own cable and connector. With USB, one standard lets you plug in almost anything.
MCP does something similar for AI. Without it, connecting an AI assistant to your invoicing system, your spreadsheets and your CRM means three separate custom integrations, one per tool and per assistant. With MCP, each tool connects once through its MCP server, and any compatible assistant can use it.
The picture, simplified:
AI assistant ↔ MCP server ↔ your tool or your data
The examples below are illustrative, just to show the idea.
What it's for, with examples
On its own, an AI assistant only knows what it learned in training and what you paste into the chat. With an MCP server, and within the permissions you set, it can:
- Look up your online store's inventory and answer "how many of this product are left?"
- Read a folder of company documents and summarize the contracts expiring this month.
- Search your customer database and draft a follow-up email.
- Create a task in your project tool when someone asks for it in the chat.
An MCP server can offer three kinds of things to the AI:
- Tools: actions the AI can run, like creating a record or running a query.
- Resources: data the AI can read, like files or records.
- Prompts: ready-made templates for common tasks.
Is it the same as an API?
Not quite. An API is the door one program uses to talk to another. It's specific to each service, and developers are the ones who use it. An MCP server usually calls those APIs underneath, but presents them to the AI in a standard way, with descriptions the model can understand.
Put differently: the API tells a developer how to call something. The MCP server tells the AI what it can do and when it makes sense to use it. MCP doesn't replace APIs. Most MCP servers rely on one.
What are the risks?
Giving an AI access to your systems is powerful, which is why it deserves care. Before connecting anything, check:
- Least privilege. The server should only do what's needed. If reading is enough, it shouldn't be able to delete.
- Accounts in your name. Credentials should belong to your company, not a third party.
- What data leaves. Know what information is sent to the model and whether it includes customer data.
- Human approval. For sensitive actions (payments, deletions, bulk emails), a person should confirm.
- Logs and limits. A record of what the AI did, plus caps on spend or usage.
Installing any MCP server you find online without checking it is like installing an unknown program on your company computer. Prefer official ones from the provider, or ones built by someone you trust.
When does it make sense for you?
An MCP server is worth it when:
- Your team already uses AI and spends the day copying data between systems.
- You have your own system (an app, a database) and want AI to query it safely.
- You want to automate repetitive tasks people do today, with oversight.
You probably don't need one yet if you're just getting started with AI and your use cases fit in a normal conversation. Start there, and connect systems once the value is clear.
How we approach it at GU Consulting
When a client wants to connect AI to their systems, we always start with a Discovery Sprint: a short, paid piece of work where we work out which use cases make sense, what data is involved, what permissions are needed, and what it would cost to build. After that, you decide whether to continue, with scope and quote in writing. Everything stays in your name: accounts, access and code.
If you want to explore whether an MCP server makes sense in your case, tell us about your project and we'll reply within 24 hours. You can also see how we work on Services and pricing.