The Orchestration of Multi-Agent Systems: Architectures, Protocols, and Enterprise Adoption
This work addresses the challenges of low coordination efficiency, lack of auditability, and insufficient policy compliance in multi-agent systems for complex tasks by proposing a unified orchestration framework that integrates planning, policy execution, state management, and observability mechanisms. The framework introduces two novel protocols—the Model Context Protocol and Agent2Agent Protocol—to enable standardized, extensible communication among agents and between agents and external tools. By supporting policy governance and end-to-end traceability, the proposed architecture provides a practical, transparent, and accountable blueprint for deploying large-scale multi-agent systems within enterprise AI ecosystems.
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