C. Bryczek, M. Macias
Jama Software, Oregon, United States
Keywords: Governed AI Workflows, Digital Thread Continuity, Modular Open Systems Approach (MOSA), Model Context Protocol (MCP), Spec-Driven Development
Regulated engineering domains, including aerospace, defense, medical, and automotive, require advanced AI-assisted development workflows. These workflows must interact with live product data without compromising configuration control, traceability, compliance, or modular open systems objectives. To solve this challenge, the abstract proposes a Model Context Protocol (MCP)-based integration architecture. This framework functions as an interoperable interface layer, exposing a governed product graph to AI agents and developer tools for controlled read and write operations. The architecture strictly enforces permission-aware data access, lifecycle-state rules, version integrity, and detailed audit logging to maintain complete digital thread continuity. By establishing semantic linkages across specifications and heterogeneous tools, the MCP layer grounds AI actions in explicit system relationships rather than unstructured text. This structured context drastically improves LLM inference quality. The architecture directly supports Spec-Driven Development by enabling automated requirement retrieval, exact code-to-requirement tracing, and thorough impact analysis. Ultimately, this governed AI approach aligns tightly with Modular Open Systems Approach (MOSA) principles. It empowers engineering teams to achieve faster iteration cycles and interface-aware modularity, all while preserving the undeniable evidence and design assurance required for safety-critical, regulated project delivery.