What Is Model Context Protocol (MCP)?

The Model Context Protocol is an open standard, introduced by Anthropic in November 2024, for connecting AI models to the tools, data, and systems they need to be useful. The easiest way to understand it is through the metaphor most people in the space now reach for: MCP is "USB-C for AI." Before USB-C, plugging a device into a computer meant hunting for the right proprietary cable. MCP solves the equivalent problem for AI — before it existed, every AI application that wanted to talk to an external tool (a database, a calendar, a codebase, a CRM) needed a custom, one-off integration built specifically for that pairing. That sounds like a minor inconvenience until you do the math. If you have ten AI applications and a hundred tools they might each want to use, the naive approach requires up to a thousand separate integrations — and every new tool or every new AI application multiplies that number further. Integration complexity was scaling quadratically just as the number of both AI agents and business tools was exploding. MCP replaces that tangle with a single, standardized interface: a tool built to speak MCP can be plugged into any MCP-compatible AI application, and an AI application that speaks MCP can reach any MCP server, without bespoke wiring in either direction. Structurally, MCP defines a client-server relationship. An "MCP server" exposes a set of capabilities — tools it can call, data it can retrieve, prompts it can offer — through a standardized protocol. An "MCP client," typically embedded in an AI application, discovers and uses those capabilities on the model's behalf. The protocol itself has kept evolving: its governance now sits with the Linux Foundation's Agentic AI Foundation, giving it a vendor-neutral home, and a new specification — covering a more stateless protocol core, formal extensions, long-running tasks, and hardened authorization — is set to finalize in late July 2026. Why Every AI Startup Is Talking About MCP The short answer is that MC