An MCP server is a small program that lets an AI assistant use an outside system, such as a calendar, a database or a shop's order list. MCP stands for Model Context Protocol, an open standard Anthropic introduced in November 2024. The server speaks this shared protocol, so any assistant that supports MCP can plug into it without custom wiring.
How an MCP server talks to an assistant
There are two sides. The client lives inside the AI application, for example Claude Desktop or a code editor. The server wraps one service and describes what it offers. Messages between them use JSON-RPC, a simple request and response format written in JSON.
A server can offer three kinds of things. Tools are actions the model may call, like "create invoice". Resources are data the client can read, like a file or a record. Prompts are reusable templates. When a conversation starts, the client asks the server what it has, and the model then decides when a tool would help. A server can run on your own computer, talking over standard input and output, or on a remote host reached over HTTP, usually with OAuth for sign-in.
A florist's spreadsheet, connected once
Say a florist keeps orders in a spreadsheet and wants to ask an assistant "which deliveries are due tomorrow?" Without MCP, someone would build a one-off integration for each AI product. With an MCP server for the spreadsheet, the florist adds it to their assistant once. The assistant lists the server's tools, calls the one that reads rows, and answers in plain English. The same server works in any other MCP-compatible client.
MCP compared with a regular API
An MCP server usually sits on top of an existing API. The API is built for programmers who read its documentation. The MCP layer adds names and descriptions that a model can read and reason about, so the model can pick the right action itself. That is why MCP matters most for AI agents that take several steps on their own.
Do you need an MCP server for your business?
Most owners will use MCP servers rather than build them: connecting an assistant to email, files or a CRM. If you sell software or run a booking service, offering an MCP server lets customers manage their account through the AI tools they already use. If neither applies, you can ignore it for now.
Mistakes people make with MCP servers
- Installing servers from unknown sources. A server runs with whatever access you grant, so treat it like any program you install.
- Granting write access by default. Start read-only and add actions like delete or send once you trust the setup.
- Vague tool descriptions. The model chooses tools by their descriptions; unclear ones get called at the wrong time.
- Too many tools at once. Dozens of connected tools crowd the model's context and make choices worse.