AIMay 28, 2025

AgentDNS: A Root Domain Naming System for LLM Agents

arXiv:2505.22368v15 citationsh-index: 3
Originality Incremental advance
AI Analysis

This addresses interoperability and communication challenges for developers and organizations using multi-agent systems, though it appears incremental as it builds on existing protocols.

The paper tackles the lack of standardized service discovery for LLM agents across vendors by proposing AgentDNS, a root domain naming system that enables autonomous discovery and secure invocation of third-party services, demonstrated through architecture and use cases.

The rapid evolution of Large Language Model (LLM) agents has highlighted critical challenges in cross-vendor service discovery, interoperability, and communication. Existing protocols like model context protocol and agent-to-agent protocol have made significant strides in standardizing interoperability between agents and tools, as well as communication among multi-agents. However, there remains a lack of standardized protocols and solutions for service discovery across different agent and tool vendors. In this paper, we propose AgentDNS, a root domain naming and service discovery system designed to enable LLM agents to autonomously discover, resolve, and securely invoke third-party agent and tool services across organizational and technological boundaries. Inspired by the principles of the traditional DNS, AgentDNS introduces a structured mechanism for service registration, semantic service discovery, secure invocation, and unified billing. We detail the architecture, core functionalities, and use cases of AgentDNS, demonstrating its potential to streamline multi-agent collaboration in real-world scenarios. The source code will be published on https://github.com/agentdns.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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