Why Anthropic's open hardware move exploded in interest

Anthropic announced its Model Hardware Standard (MHS) at the end of August as an open interface for connecting AI models and agents to hardware, and received 30x more organizations requesting to participate in the first two weeks than it had planned for, according to Alek Kemeny, a member of technical staff on Anthropic's Beneficial Deployments team. Anthropic positions MHS as "the MCP for hardware," extending the Model Context Protocol it open-sourced in November 2024, which now sees around 500 million monthly SDK downloads. Early adopters include QuEra, which used MHS to have Claude write a laser-control program that restored the laser correctly in 695 of 700 tests, with difficult recoveries taking 10 to 14 seconds versus 5 to 10 minutes for a human expert, and Carnegie Mellon researchers who connected a liquid handler, plate reader, robotic arm, and cameras so an AI agent could run and adjust an experiment autonomously.

nthropic is the only one of three major frontier AI labs in the US that doesn't offer an open model. But a recent Anthropic move shows that the company does still want to support open ecosystems. In a move that has largely flown under the radar, Anthropic announced https://www.anthropic.com/news/model-hardware-standard-research-preview its Model Hardware Standard MHS at the end of August as "the MCP for hardware," as Alek Kemeny, a member of technical staff on Anthropic's Beneficial Deployments team, told The Deep View. MCP Model Context Protocol is an open standard that enables AI models and agents to connect to external tools, data, and services through a common interface that Anthropic developed and open-sourced in November 2024. It has since become an industry standard with around 500 million monthly SDK downloads https://blog.modelcontextprotocol.io/posts/2026-07-28/ , and has only become more relevant in recent months with the rise of AI agents that are hungry for context and data. MHS hopes to do for hardware and devices what MCP has done for software and services. It wants to give AI models and agents a common interface for interacting with thousands of otherwise incompatible systems. While MHS was conceived as a way for scientists to drive lab automation using Claude, the response to the announcement has been intense, the Anthropic team said, and has spread far beyond science labs. Kemeny noted that in the first two weeks after the announcement, Anthropic received 30x the number of organizations requesting to participate than Anthropic had originally planned for. And the types of organizations that applied spanned a lot of different industries from semiconductors, advanced manufacturing, automotive, food processing, aerospace, energy, and critical infrastructure. Some of the benefits already being reported include: - Stabilizing quantum computers : QuEra https://www.quera.com/ used MHS to help Claude develop a program for controlling lasers used in its quantum computers. The finished program restored the laser correctly in 695 of 700 tests. Difficult recoveries took 10 to 14 seconds, compared with 5 to 10 minutes for a human expert. - Running lab experiments automatically : Carnegie Mellon researchers used MHS to connect a liquid handler, plate reader, robotic arm, and cameras. An AI agent ran an experiment, decided the first result was not good enough, changed the concentration range and tried again on its own. The test used colored dye as a stand-in for a drug candidate. CMU says testing real drug candidates is the next step. - Giving labs a 24/7 operator : A University of Washington PhD student connected six lab instruments through MHS in less than a week. He built a system where AI can watch a DNA amplification experiment and stop it at the right time. He also connected a robotic arm and liquid handler so they could move lab plates safely between machines. "Beneficial Deployments is really charged with seeing, owning, and championing our public benefit mission, and ensuring that the benefits of AI extend to positive outcomes for humanity," Jonah Cool, head of our partnerships and deployment at Anthropic, told The Deep View during the same interview with Kemeny. "As it pertains to science, a lot of our work is really inspired by the guiding light of the essay that our CEO Dario Amodei wrote, Machines of Loving Grace https://darioamodei.com/essay/machines-of-loving-grace ." Our Deeper View Anthropic has gained a reputation for being anti-open-source, mostly due to the fact that Amodei has raised safety concerns about open-weights models https://www.anthropic.com/news/position-open-weights-models . However, the successful open-source rollout of MCP provides a counterweight, as does Anthropic's commitment to and support for the scientific community, which tends to lean on open ecosystems for the purposes of both sharing research and verifying results. Anthropic still describes MHS as being an application-only research preview. But they asserted that they intend to open-source MHS in the hope of it becoming an industry standard like MCP. Kemeny and Cool explained that they're first working with industry partners to test safety and security while the models are now operating on real-world equipment. It's also a fun note that since Cool has a PhD in cell biology, one of the leaders of this initiative is essentially named Dr. Cool. That kind of marketing is nearly as good as making it an open platform.