What Is an MCP Server? A Plain-English Guide

MCP stands for Model Context Protocol. It's an open standard released by Anthropic that lets AI assistants connect directly to external tools, databases, and services.

Think of it as a universal adapter for AI. Instead of every AI tool building its own integration system, MCP provides a standard way for any AI assistant to talk to any service.

An MCP server is a lightweight program that sits between your AI assistant and a service (like GitHub, a database, or a search engine). It translates the AI's requests into actions, and returns results in a structured format the AI can understand.

Why does this matter? Before MCP, each AI tool had its own plugin system. Claude had one format, ChatGPT had another, and so on. Developers had to build separate integrations for each. MCP unifies this — build once, use everywhere.

MCP servers use a client-server architecture. Your AI assistant is the client. It connects to MCP servers (either running locally or remotely) and calls their tools. The servers handle the actual work: querying databases, fetching web pages, managing files, etc.

The protocol supports two transport mechanisms: stdio (running the server as a local process) and HTTP/SSE (connecting to remote servers). Most developer tools use stdio for security and simplicity.

Getting started is simple. Most MCP servers can be installed with a single command like `npx @github/github-mcp-server`. Add a config entry to your AI client's settings, and you're ready to go.