MCP is an open standard, introduced by Anthropic, that defines how AI models connect to external tools, data sources, and services — the plumbing that lets an AI agent actually do things instead of just talk about them.
Definition
MCP standardizes the interface between a model and the systems it acts on: a server exposes tools and data in a defined format, and any MCP-compatible agent can use them. For advertising, it's foundational infrastructure — AdCP is built on it — because agentic media buying requires agents to read inventory, query data, and execute actions across many parties' systems without custom integration for each pair.
Why it matters
Before MCP, every AI-to-system connection was a bespoke integration; after it, capabilities become plug-in. That collapses the cost of giving agents real execution ability — which is exactly why agentic advertising accelerated once the protocol layer existed. Understanding MCP explains why 'AI that acts' arrived across the industry nearly simultaneously.
In agentic execution
Protocol-standardized execution is the world Adlyse is built for: agents that act on ad platforms through defined, auditable interfaces, with human approval gating what actually ships.
Related terms
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