Building for the Model Hardware Standard

Anthropic’s emerging Model Hardware Standard, based on lessons from the Model Context Protocol, aims to provide a shared way for AI agents to safely control physical equipment such as robot arms, laboratory instruments, and manufacturing machinery. Unlike software-focused agent protocols, hardware control introduces higher risks because delayed or repeated commands can damage materials, wear out devices, or compromise scientific experiments. Building on its edge MCP implementation, Fastly has developed a research prototype that retains existing authentication, authorization, and schema-validation capabilities while adding device-specific safety-limit checks, per-device command quotas, and privacy-conscious audit trails. Although the standard remains in an early stage, the work highlights the need for reliable network performance, strong end-to-end security, and coordinated controls across software and physical systems as AI agents increasingly interact with real-world hardware.

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