NANDA Adaptive Resolver: Architecture for Dynamic Resolution of AI Agent Names

TL;DR

AdaptiveResolver introduces a dynamic, context-aware architecture for real-time resolution of AI agent communication endpoints, enhancing flexibility, security, and scalability in distributed environments.

Contribution

It proposes a novel microservice architecture enabling real-time, context-based resolution of agent names, surpassing static DNS or URLs for AI agent communication.

Findings

Supports real-time, context-aware endpoint resolution

Enables negotiation of trust and quality of service

Facilitates secure, scalable agent interactions

Abstract

AdaptiveResolver is a dynamic microservice architecture designed to address the limitations of static endpoint resolution for AI agent communication in distributed, heterogeneous environments. Unlike traditional DNS or static URLs, AdaptiveResolver enables context-aware, real-time selection of communication endpoints based on factors such as geographic location, system load, agent capabilities, and security threats. Agents advertise their Agent Name and context requirements through Agent Fact cards in an Agent Registry/Index. A requesting Agent discovers a Target Agent using the registry. The Requester Agent can then resolve the Target Agent Name to obtain a tailored communication channel to the agent based on actual environmental context between the agents. The architecture supports negotiation of trust, quality of service, and resource constraints, facilitating flexible, secure, and scalable agent-to-agent interactions that go beyond the classic client-server model. AdaptiveResolver provides a foundation for robust, future-proof agent communication that can evolve with increasing ecosystem complexity.