A Survey of AI Agent Registry Solutions

• URL: http://arxiv.org/abs/2508.03095v1
• Date: Tue, 05 Aug 2025 05:17:18 GMT
• Title: A Survey of AI Agent Registry Solutions
• Authors: Aditi Singh, Abul Ehtesham, Ramesh Raskar, Mahesh Lambe, Pradyumna Chari, Jared James Grogan, Abhishek Singh, Saket Kumar,
• Abstract summary: As autonomous AI agents scale across cloud, enterprise, and decentralized environments, the need for standardized registry systems has become essential.<n>This paper surveys three prominent registry approaches each defined by a unique verifiable metadata model: MCP's mcp., A2A's Agent Card, and NANDA's AgentFacts.<n>The paper concludes with suggestions and recommendations to guide future design and adoption of registry systems for the Internet of AI Agents.
• Score: 10.500986125166454
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: As As autonomous AI agents scale across cloud, enterprise, and decentralized environments, the need for standardized registry systems to support discovery, identity, and capability sharing has become essential. This paper surveys three prominent registry approaches each defined by a unique metadata model: MCP's mcp.json, A2A's Agent Card, and NANDA's AgentFacts. MCP uses a centralized metaregistry with GitHub authenticated publishing and structured metadata for server discovery. A2A enables decentralized interaction via JSON-based Agent Cards, discoverable through well-known URIs, curated catalogs, or direct configuration. NANDA Index introduces AgentFacts, a cryptographically verifiable and privacy-preserving metadata model designed for dynamic discovery, credentialed capabilities, and cross-domain interoperability. These approaches are compared across four dimensions: security, scalability, authentication, and maintainability. The paper concludes with suggestions and recommendations to guide future design and adoption of registry systems for the Internet of AI Agents.

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