The article examines the architectural role of the Model Context Protocol in the design of multi-agent systems intended to support robust coordination between cognitive and infrastructural components. The relevance of the study is determined by the rapid transition from isolated LLM interactions to distributed agentic environments, in which direct coupling between agents and external APIs, data sources, and tools increases system interdependence, complicates maintenance, and weakens governability. The purpose of the article is to provide a conceptual substantiation of the architectural principles of multi-agent systems based on MCP and to identify their significance for scalability, interoperability, security, and maintainability. The scientific novelty of the study lies in interpreting MCP not merely as an auxiliary integration protocol, but as an autonomous architectural layer that establishes a formalized topology of interaction among hosts, clients, and servers. The principal findings demonstrate that the use of MCP ensures a strict separation of concerns, declarative context management, modular composability, and governance-by-design in capability access. The article concludes that such an approach enhances observability, reduces integration fragility, and creates the foundation for the evolutionary development of multi-agent solutions while preserving control and auditability. The article will be useful for researchers, AI system architects, developers of agentic platforms, and specialists in enterprise digital infrastructure.

multi-agent systems, Model Context Protocol, AI architecture, interoperability, modularity, security

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