标题： AI代理注册解决方案综述 显示英文标题

标题： A Survey of AI Agent Registry Solutions

摘要： 随着自主AI代理在云、企业及去中心化环境中扩展，建立标准化注册系统以支持发现、身份和能力共享的需求变得至关重要。 本文综述了三种突出的注册方法，每种方法由独特的元数据模型定义：MCP的mcp.json，A2A的Agent Card，以及NANDA的AgentFacts。 MCP使用带有GitHub认证发布的集中式元注册表，并为服务器发现提供结构化元数据。 A2A通过基于JSON的Agent Cards实现去中心化交互，可通过众所周知的URI、精选目录或直接配置进行发现。 NANDA Index引入了AgentFacts，这是一种密码学可验证且隐私保护的元数据模型，专为动态发现、凭据能力及跨域互操作性而设计。 这些方法在四个维度上进行了比较：安全性、可扩展性、认证和可维护性。 本文最后提出了建议和推荐，以指导未来针对AI代理互联网的注册系统的设计和采用。 显示英文摘要

摘要： 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.