What MCP Actually Is (And Why It Matters)
If you've been paying attention to AI tooling lately, you've probably seen "MCP" mentioned. Usually without much explanation. So let me fix that.
MCP stands for Model Context Protocol. It's an open standard from Anthropic that lets AI assistants connect to external data sources and tools. That's basically it.
Why this matters
Right now, most AI tools are isolated. You start a conversation with Claude, and it only knows what's in its training data plus whatever you paste into the chat window. Same with ChatGPT, Gemini, or any other assistant.
That's limiting. Your AI can't see your files. It can't access your databases. It can't check your calendar or read your notes. Every conversation starts from scratch.
MCP changes that.
With MCP, an AI assistant can connect to external "servers" that provide context and capabilities. A server might give access to your Google Drive, your GitHub repos, your company's internal docs, or a specialized database. The AI requests what it needs, the server provides it, and suddenly the AI has relevant context it didn't have before.
How it works (simplified)
There are three pieces:
- MCP Hosts - The AI applications you use (Claude Desktop, Cursor, etc.)
- MCP Servers - Programs that expose data or tools to AI (could be local on your machine or remote)
- The Protocol - How they communicate (JSON-RPC over stdio or HTTP)
When you connect an MCP server to your AI tool, you're giving that tool access to whatever the server provides. It might be read-only access to files. It might be the ability to run code. It might be search across a specific dataset.
The AI doesn't get blanket access to everything - servers define what they expose, and you control which servers are connected.
Why Anthropic open-sourced it
This is the interesting part. Anthropic could have kept this proprietary - a competitive advantage for Claude. Instead, they published the full specification and made it available to everyone.
The thinking: if MCP becomes a standard, every AI tool benefits from a growing ecosystem of compatible servers. Developers build once, and their integration works everywhere.
It's early. Not every AI tool supports MCP yet. But Claude Desktop, Cursor, and several others already do, and momentum is building.
What this means practically
For most people, MCP is still behind the scenes. You might use an AI tool that's MCP-enabled without knowing it.
But if you're building with AI - or if you want your AI tools to work together better - MCP is the infrastructure that makes it possible. It's how your AI stops being a disconnected chat window and starts being something that actually knows about your work.
I've been building with MCP for a few months now, and it's changed how I think about AI tooling. More on that soon.