AgentGate: A Lightweight Structured Routing Engine for the Internet of Agents
Summary: arXiv:2604.06696v1 Announce Type: new
Abstract
The rapid development of AI agent systems is leading to an emerging Internet of Agents, where specialized agents operate across local devices, edge nodes, private services, and cloud platforms. Although recent efforts have improved agent naming, discovery, and interaction, efficient request dispatch remains an open systems problem under latency, privacy, and cost constraints.
In this paper, we present AgentGate, a lightweight structured routing engine for candidate-aware agent dispatch. Instead of treating routing as unrestricted text generation, AgentGate formulates it as a constrained decision problem and decomposes it into two stages: action decision and structural grounding.
Key Features of AgentGate
The architecture of AgentGate is designed to optimize the dispatch of requests among various agents efficiently. Here are the key features:
- Action Decision: This stage determines whether a query should trigger a single-agent invocation, multi-agent planning, direct response, or safe escalation.
- Structural Grounding: Once the action is decided, this stage instantiates the selected action into executable outputs such as target agents, structured arguments, or multi-step plans.
- Routing-Oriented Fine-Tuning: To adapt compact models to this setting, we further develop a routing-oriented fine-tuning scheme with candidate-aware supervision and hard negative examples.
Performance Insights
Experiments conducted on a curated routing benchmark with several 3B–7B open-weight models have yielded promising results. The findings indicate that:
- Compact models can provide competitive routing performance in constrained settings.
- Model differences are predominantly reflected in action prediction, candidate selection, and the quality of structured grounding.
- The structured routing approach is a feasible design point for developing efficient and privacy-aware agent systems.
Conclusion
As the Internet of Agents continues to evolve, the need for efficient routing mechanisms becomes increasingly critical. AgentGate stands out as a promising solution that addresses the challenges of latency, privacy, and cost in agent dispatch systems. By leveraging a structured approach to routing, AgentGate not only enhances the performance of compact models but also sets a foundation for future advancements in the field.
These results suggest that structured routing can significantly improve agent interactions, particularly when decisions must be made under resource-constrained deployment conditions. The ongoing development and refinement of AgentGate will undoubtedly contribute to the growing ecosystem of AI agent systems.