Definition
Model Context Protocol is the Model Context Protocol (MCP) is an open standard that lets AI apps connect to outside tools and data through one common interface, so a tool built once works with many different AI models.
The Model Context Protocol, usually shortened to MCP, is an open standard for connecting AI applications to the tools and data they need. Anthropic introduced it in late 2024, and many other AI companies and developers have since adopted it.
Think of a USB port. Before USB, every device needed its own cable and its own driver. MCP does the same job for AI: instead of writing a custom connection between every AI app and every service, a developer builds one MCP connection and any app that speaks the protocol can use it.
MCP has two sides. An MCP server wraps something useful, such as a calendar, a database, a code repository or a company wiki, and describes what it can do. An MCP client lives inside an AI app, such as a chat assistant or a coding tool, and lets the model discover those abilities and call them.
A server can offer three kinds of things:
When you ask a question, the model sees which tools are available, decides whether one would help, and asks the client to call it. The result comes back as text the model can read, which uses up part of its context window. The model never gets direct access to your systems. The client and server sit in between and apply the permissions you set.
MCP is what turns a chatbot into an AI agent that can actually do things in your software. It also reduces lock-in. If your tools speak MCP, you can switch the AI model or the app on top without rebuilding every integration.
Because an MCP server can act on your behalf, you should treat each one like an app you install. Connect only servers you trust, give them the narrowest access that works, and check what they can change. Text returned by a tool can also contain hidden instructions meant to trick the model, an attack called prompt injection, so sensitive actions deserve a human confirmation step.
Say you connect a project-tracker MCP server to your assistant. You ask, "What is overdue on the launch board?" The assistant calls the server's search tool, reads the results and answers in plain English. Ask it to move a task and it calls a different tool, ideally after asking you first.
MCP sits next to tokens and context limits in practice, because every tool description and every result costs tokens. Teams that use many servers often watch that cost and use prompt caching to keep it down.
Anthropic introduced MCP in late 2024 as an open standard. Other AI companies and tool makers have since added support for it.
No. An API is one service's own interface. MCP is a common layer on top that lets an AI app discover and call many services in the same way.
It can be, if you connect only trusted servers, limit their permissions and require confirmation for risky actions.
Figma released Specs in open beta for paid plans on Oct. 15, a doc on the canvas that its own agent and outside coding agents can read through MCP. Agents fail on missing context, and Figma wants to be where that context lives.
Walmart opened a beta Agent Gateway for AI shopping agents and says Agent Profiles with approvals and spending caps arrive within a month, while agents never see your card. With Amazon blocking agents, the biggest US retailers just split.
Apple says a November update adds Model Context Protocol support to Keynote, Pages and Numbers on macOS 27, so outside AI agents can read, edit and automate your documents. The built-in assistant gets the attention. The open door for your own agent matters more.