What is MCP?

MCP (Model Context Protocol) is an open standard, introduced by Anthropic in late 2024, for connecting tools and data to AI models. Think of it as the USB-C port of AI.

The problem MCP solves

Before MCP, every time you wanted to give an AI app access to a new tool. Gmail, GitHub, your local file system, someone had to write custom glue code. That glue was non-portable: it worked with one app and one model, and had to be rewritten for the next.

MCP standardizes the glue. Write one MCP server for Gmail and any MCP-speaking client (Claude Code, Claude.ai, other agents) can use it. Build once, plug in anywhere.

The one-sentence pitch

"A standard way for AI agents to discover and use external tools and data."

What MCP actually does

An MCP server exposes three things to an MCP client:

The client (e.g. Claude Code) connects to the server, asks what's available, and makes those tools/resources/prompts available to the model.

Why it matters for autonomy

Autonomous agents need many tools to do real work. Without MCP, connecting an agent to 20 services means writing 20 custom integrations and maintaining them as APIs change. With MCP, you install 20 pre-built servers (your own or from the community) and the agent uses them immediately.

Insight: MCP doesn't make a model smarter. It multiplies what the model can reach. That's what makes autonomous work viable.

Who uses MCP today

Who builds MCP servers

What MCP is NOT

What to read next

Head to Anatomy to understand the five primitives, or jump to Directory for a curated list of MCPs worth trying.