The Model Context Protocol (MCP) is shifting from a stateful to a fully stateless architecture to accommodate the massive scale required by hyperscalers. This transition replaces persistent sessions with a stateless transport mechanism, utilizing "multi-roundtrip responses" to manage necessary stateful interactions, such as user input elicitation, without maintaining open connections. As models have improved, they can now handle implicit sessions by carrying IDs across tool calls, allowing the protocol to shed unnecessary complexity. Development strategy now focuses on maintaining a stable, minimalist core while offloading experimental features like long-running tasks to independent extensions. This evolution prioritizes long-term stability and composability, ensuring the protocol remains a robust, standard component of the AI infrastructure stack while minimizing the friction of future updates for developers.
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