MCP (Model Context Protocol)
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One standard plug between AI and your systems. The plug is easy. Deciding what it reaches is not.
1. Quick Answer
MCP, the Model Context Protocol, is an open standard for connecting AI models to tools, data, and systems through one consistent interface. A server exposes capabilities, the model acts as a client that discovers and calls them. It replaces the tangle of custom one-off integrations that previously connected every model to every system.
2. What is MCP?
MCP standardizes the connection between an AI system and the things it needs to do real work. The common analogy is a universal port: one interface, many devices, no bespoke wiring per device.
The architecture has three roles worth knowing by name, because they are where the design decisions live:
Server, Wraps a system, a database, a file store, an API, a SaaS product, and exposes specific capabilities through the protocol.
Client, The AI application that discovers what a server offers and calls it.
Transport, The connection between them, which can be local to a machine or remote over the network.
The practical shift is in integration count. Connecting three assistants to four internal systems used to mean up to twelve custom connectors, each with its own auth and error handling. With a standard, it means four servers that any compliant client can use. The integration work moves from N×M to N+M, which is the entire economic argument.
