An Overview of Messaging Systems and Their Applicability to Agentic AI

Agentic AI systems require messaging infrastructure that supports real-time collaboration, high-volume streaming, and dynamic group coordination across distributed networks. Traditional protocols like AMQP, MQTT, and NATS address some requirements but fall short on security, particularly regarding [AMQP] [MQTT] [NATS] post-compromise protection and quantum-safe encryption essential for autonomous agents handling sensitive data. This document analyzes six messaging protocols—AMQP, MQTT, NATS, AMQP over WebSockets, Kafka, and AGNTCY SLIM—across dimensions critical for GenAI agent systems: streaming performance, delivery guarantees, security models, and operational complexity. We examine how each protocol's design decisions impact agentic AI deployments, from lightweight edge computing scenarios to large-scale multi- organizational collaborations. AGNTCY SLIM emerges as a purpose-built solution, integrating Message Layer Security (MLS) [RFC9420] with gRPC [gRPC] over HTTP/2 [RFC7540] to provide quantum-safe end-to-end encryption, efficient streaming, and OAuth-based authentication [RFC6749]. Unlike transport-layer security approaches, SLIM's MLS implementation ensures secure communication even through untrusted intermediaries while supporting dynamic group membership changes essential for collaborative AI agents.