MCP
Model Context Protocol
An open protocol that lets an AI assistant call external tools and read external data through a uniform interface, instead of each integration being built by hand.
What makes it wrong.
The mechanism, not the warning.
MCP standardises the plumbing, not the quality of what flows through it. Two servers for the same advertising API can expose wildly different surfaces, one with four hundred generated tools and one with thirty written by hand, and the protocol has nothing to say about which will actually answer a question. The compatibility promise is about clients, never about capability.
In detail.
MCP standardises the shape of the connection between a model and everything outside it. A server exposes tools, resources and prompts; a client, which is the assistant application, discovers them at connection time and can then call them during a conversation. The model itself never talks to the advertising API: it decides which tool to call and with what arguments, and the client performs the call.
The practical consequence is that an integration written once works in every client that speaks the protocol. A Google Ads server built for Claude works in Cursor, in ChatGPT and in an n8n workflow, without a second implementation.