Boundary Interfaces and Machine-Entity Relations

Boundary Interfaces and Machine-Entity Relations proposes an implementation-neutral public interoperability profile for governed interaction between AI agents, data services, knowledge systems and other machine-readable information environments. The paper examines the boundary at which one system, organization, agent or user interacts with another. It argues that a useful public boundary should expose not only content but also selected conditions required for responsible interpretation, including identity, relation type, provenance, evidence status, context, limitations, response status and version. The paper introduces the Machine-Entity Boundary Profile, or MEBP, as a conceptual profile. MEBP describes how an external agent may request and interpret public information about entities, relationships, evidence, state and governance boundaries without requiring access to internal architecture, source code, model weights, training data, private schemas, federation topology, routing logic, authorization mechanisms or proprietary methods. The proposed request classes cover entity, relation, evidence, state and boundary requests. The response model distinguishes available, qualified, partial, ambiguous, contradicted, superseded, insufficient-evidence, out-of-scope, unauthorized and unavailable responses. The profile treats relations as typed, directional and contextual. Its proposed public relation vocabulary includes references, cites, follows, followed_by, related_to, defines, uses_vocabulary_from, operationalizes, derived_from, supersedes and contradicts. A declared relation does not automatically establish endorsement, certification, legal effect, commercial partnership or independent validation. The paper also distinguishes six conceptual evidence grades: declared, implemented, runtime observed, persistent, causally witnessed and independently evaluated. An evidence grade describes the support for a specific claim; it does not establish broad truth, security, regulatory compliance, institutional legitimacy or universal system reliability. The illustrative response structure may be represented through JSON, JSON-LD, structured HTML, API responses, tool responses, agent interaction patterns or other machine-readable formats. It is not a mandatory schema, production endpoint, network protocol or technical standard. The paper discusses principles relevant to systems interacting with Model Context Protocol-compatible and other agent-tool environments. It does not define, modify or claim adoption by Model Context Protocol, and it does not require a specific protocol, database, graph architecture, AI model, storage method or federation design. A governed public boundary may disclose enough metadata to make a response interpretable while withholding private personal data, internal identifiers, credentials, authorization details, security-sensitive locations, private evidence records, client information and non-public system state. This is Paper 3 of the Morphogenic Systems Research Series. It builds on the conceptual distinction established in Built Systems and Morphogenic Systems and the evaluation framework developed in Black-Box Behavioral Conformance for Morphogenic Systems. Publication status: Independent technical report. The work is conceptual and implementation-neutral. It is not an RFC, Internet Standard, IETF-approved document, working-group document, W3C specification, ISO standard, certification program, regulatory determination, security audit, peer-reviewed journal article or claim of independent validation.