Artificial intelligence company Anthropic has recently officially launched the MCP standard for hardware - the Model Hardware Standard. As a new standard aimed at helping large model-driven AI agents safely and efficiently operate physical devices, MHS is seen as a crucial step in bridging the gap between virtual and real worlds for AI technology.

This standard originated from a deep collaboration between Anthropic and the Janelia Research Campus of the Howard Hughes Medical Institute. It is now available in a research preview version for the first batch of research laboratories and advanced manufacturers. In practical applications, MHS has demonstrated remarkable efficiency improvements, significantly reducing the time required for hardware integration from weeks or even months to hours or minutes, greatly lowering the technical barriers for scientific research and industrial automation.

In terms of core functions and collaborative performance, MHS helps researchers and engineers easily coordinate autonomous round-the-clock experiments and workflows. During testing, Claude connected to this standard showed exploratory behavior similar to that of human scientists. The AI agent not only can autonomously reason about experimental steps and dynamically update various parameters, but it can also recover from unexpected hardware failures without any human intervention.

In terms of hardware compatibility and control mechanisms, MHS has high versatility. It can adapt to any physical device with a programmable interface, and is independent of the type of underlying base model. Through a unified standardized driver, the standard effectively solves industry challenges such as device communication and interaction with agents, even allowing agents to autonomously understand unfamiliar devices. Currently, MHS mainly provides three specific mechanisms for controlling hardware: MCP, command-line interface, and code files.

Although showing great application potential, MHS still has certain limitations at this stage, such as the inability to fully support traditional hardware without programmable interfaces. In response, Anthropic is actively working on improving the standard, and many early adopters are also actively participating in related testing and integration, jointly promoting AI's expansion into a broader physical world for control and collaboration.