The Agent Hub Architecture: A Framework for Resilient, Efficient, and Specialized Multi-Agent AI Orchestration
Year: 2025
Type: article
Abstract: This paper presents a comprehensive analysis of the Agent Hub platform, an enterprise-grade AI orchestration system demonstrating significant advancements in multi-agent systems (MAS), operational resilience, and Large Language Model (LLM) efficiency. We analyze its architecture, founded on the Model Context Protocol (MCP) and featuring nine specialized Al agents in a distributed intelligence model. Our evaluation validates novel engineering patterns, including proactive token optimization and reactive multi-layered circuit breaking, achieving a 75% reduction in token consumption and 99.8% rate limit compliance. We establish quantitative metrics for performance, fault tolerance, and decision accuracy, demonstrating an 80% reduction in developer context switching and 90% faster security vulnerability detection. These technical achievements translate to measurable business impact with ROI calculations ranging from 180-300%, positioning Agent Hub as a blueprint for next-generation enterprise AI systems
Author: Ginting, Nathan Aldyth Prananta
Institution: Sunway University
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7081985517
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