The Sequence Engineering #524: Why Did MCP Win?

The AI agent community could have embraced other standards, but it didn't. Why?

Anthropic’s Model Context Protocol(MCP) is everywhere! The protocol has rapidly evolved into the canonical standard for context serialization and exchange, displacing earlier contenders such as OpenAPI, GraphQL, and a host of proprietary alternatives. This essay critically examines the architecture, adoption dynamics, and ecosystem alignment that enabled MCP to prevail, providing a comprehensive analysis of its role as the foundational layer in modern Agent AI infrastructure.

Context Continuity in Multi-Agent Architectures

Agent-based systems rely on persistent context to maintain stateful interactions—spanning user intent, historical reasoning chains, environmental state, and tool usage. Initial implementations were disjointed, with custom APIs and fragmented data formats introducing brittle dependencies and limiting composability.