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A Safety-Bounded SDC-to-MCP Gateway for Medical AI Agents — arXiv:2609.31358

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.31358
License (as archived): CC0-1.0
Archived: 2026-10-08T01:39:53.702Z
SHA-256 of the archived text: 525d06637028b2f640d0668935984fa0f97672cba8502876af328b8d59bb0b89
Stable URL of this page: https://metraipolis.com/documento/dc_0ddbbfacf9e5

How to cite

A Safety-Bounded SDC-to-MCP Gateway for Medical AI Agents — arXiv:2609.31358 — arXiv (en), https://arxiv.org/abs/2609.31358 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_0ddbbfacf9e5 (Metraipolis archive dc_0ddbbfacf9e5, sha256 525d06637028b2f640d0668935984fa0f97672cba8502876af328b8d59bb0b89)

BibTeX

@misc{dc0ddbbfacf9e5,
  title = {A Safety-Bounded SDC-to-MCP Gateway for Medical AI Agents — arXiv:2609.31358},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.31358},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_0ddbbfacf9e5; sha256 525d06637028b2f640d0668935984fa0f97672cba8502876af328b8d59bb0b89},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.31358. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

The Model Context Protocol (MCP) provides a common interface through which AI applications discover and use external resources and tools. It allows language-model agents to ground their reasoning in current system state and interact with heterogeneous services. In medical environments, however, exposing device state and action affordances requires deterministic constraints on possible effects. We present an IEEE 11073 Service-Oriented Device Connectivity (SDC)-to-MCP gateway that exposes metrics, alarms, context references, and semantic metadata as read-only resources, while representing selected action affordances as policy-validated dry-run tools. The term safety-bounded denotes a narrow no-execution property: agent-facing requests dispatch no SDC device operation. A Python prototype supports simulated fault and lifecycle experiments, a software-reference protocol path spanning independent Java and Python implementations, deterministic baselines, representation ablations, and multi-model agent evaluation. The results show semantically explicit resource exposure, visible rejection of invalid or outdated state, and preservation of the no-execution boundary across resource, proposal, and authorization paths. Explicit semantic metadata improved conformity to required metric identifiers in structured alarm outputs relative to a generic representation, while retained structured-output failures reveal a distinction between plausible narrative answers and task-compliant machine-readable results.

Tema degli esploratori: agenti e intelligenza artificiale (retro-catalogo arXiv: annunci del 2026-09-28 in cs.AI).
Categorie arXiv: Distributed, Parallel, and Cluster Computing (cs.DC) ; Artificial Intelligence (cs.AI).
Pagina del lavoro: https://arxiv.org/abs/2609.31358 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-08T01:12:14.581Z dalla pagina https://arxiv.org/catchup/cs.AI/2026-09-28?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).