Model Context Protocol (MCP): What It Is and How It Works
MCP is an open standard from Anthropic that lets AI models connect to data and tools through a unified protocol - like USB for AI assistants.
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MCP stands for Model Context Protocol, an open standard announced by Anthropic that defines how models connect to data and programs. Instead of writing separate integrations for every tool-model pair, you expose an MCP server once, and any client supporting the standard can use it. The best comparison: MCP is to models what USB is to devices.
What MCP Actually Provides
- Tools - functions the model can call: search a database, send an API query, save a file.
- Resources - data for reading: files, tables, documents.
- Prompt templates - ready-made instructions that the application can suggest to you.
Why MCP Matters
Before MCP, every integration was a separate project: different ways of describing functions in one model versus another, different authentication methods. The standard removes this work and lets you move the same server between tools. In practice, you’ll most often encounter MCP in development tools, for example in Claude Code and in editors with assistants, as well as in enterprise deployments where the model needs to access internal systems.
What to Remember When Implementing MCP
An MCP server gives the model real permissions, so the same hygiene applies as with any system access: separate account with minimal privileges, confirmation of data-changing operations, and logging of calls. Connecting a server with write access to a production database “just to try it” is the shortest path to trouble.
Google · Your sourcesQuantslant higher in your Google - one clickAdd to preferred sources →Common Questions
Does MCP Only Work with Claude?
No. The standard is open and is also supported by other tools and models; Anthropic announced it but didn’t lock it down.
How Is MCP Different from a Regular API?
MCP is a description layer on top of an API: it tells the model what functions exist, what they expect, and what they return, in a form the model understands without separate programming.
Is This the Same as an Agent?
No. MCP provides access, while an agent is a way the model works that uses that access in a loop. I write about agents separately in the article on AI agents.
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