The AGNTCY Agent Directory Service: Architecture and Implementation

2025-09-23

AI Summary

Efficient, verifiable, and multidimensional discovery of AI agent capabilities, metadata, and provenance remains challenging in distributed heterogeneous multi-agent systems (MAS). Method: We propose a novel decentralized agent directory service featuring a two-tier mapping architecture that decouples capability indexing from content location; integrates a hierarchical semantic classification scheme with cryptographic signing (Sigstore); employs Kademlia-based DHT for decentralized routing; and leverages OCI/ORAS for content-addressable storage and Open Agent Protocol (OAP)-driven schema extensibility. Contribution/Results: This work presents the first secure, scalable, cross-platform agent discovery framework supporting emerging agent types—including LLM prompt agents and MCP servers. Experiments demonstrate low registration latency, high retrieval accuracy, strong interoperability, and cryptographically verifiable provenance—enabling trustworthy, dynamic agent composition in open MAS environments.

Technology Category

Multiagent Systems: Agent CommunicationCognitive Modeling & Cognitive Systems: Agent ArchitecturesSearch and Optimization: Distributed Search

Application Category

Search and Retrieval-Augmented AI: Agentic searchSystems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systemsSemantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

The Agent Directory Service (ADS) is a distributed directory for the discovery of AI agent capabilities, metadata, and provenance. It leverages content-addressed storage, hierarchical taxonomies, and cryptographic signing to enable efficient, verifiable, and multi-dimensional discovery across heterogeneous Multi-Agent Systems (MAS). Built on the Open Agentic Schema Framework (OASF), ADS decouples capability indexing from content location through a two-level mapping realized over a Kademlia-based Distributed Hash Table (DHT). It reuses mature OCI / ORAS infrastructure for artifact distribution, integrates Sigstore for provenance, and supports schema-driven extensibility for emerging agent modalities (LLM prompt agents, MCP servers, A2A-enabled components). This paper formalizes the architectural model, describes storage and discovery layers, explains security and performance properties, and positions ADS within the broader landscape of emerging agent registry and interoperability initiatives.

Problem

• Enabling efficient discovery of AI agent capabilities across heterogeneous multi-agent systems
• Providing verifiable agent metadata and provenance through cryptographic signing
• Decoupling capability indexing from content location using distributed hash tables

Innovation

• Uses content-addressed storage and cryptographic signing
• Leverages a Kademlia-based Distributed Hash Table
• Reuses OCI/ORAS infrastructure and integrates Sigstore