Autonomous AI agents now operate across cloud, enterprise, and decentralized domains, creating demand for registry infrastructures that enable trustworthy discovery, capability negotiation, and identity assurance. We analyze five prominent approaches: (1) MCP Registry (centralized publication of mcp.json descriptors), (2) A2A Agent Cards (decentralized self-describing JSON capability manifests), (3) AGNTCY Agent Directory Service (IPFS Kademlia DHT content routing extended for semantic taxonomy-based content discovery, OCI artifact storage, and Sigstore-backed integrity), (4) Microsoft Entra Agent ID (enterprise SaaS directory with policy and zero-trust integration), and (5) NANDA Index AgentFacts (cryptographically verifiable, privacy-preserving fact model with credentialed assertions). Using four evaluation dimensions: security, authentication, scalability, and maintainability, we surface architectural trade-offs between centralized control, enterprise governance, and distributed resilience. We conclude with design recommendations for an emerging Internet of AI Agents requiring verifiable identity, adaptive discovery flows, and interoperable capability semantics.
翻译:当前,自主AI智能体已在云端、企业级和去中心化领域广泛运行,这催生了对于能够支持可信发现、能力协商与身份保障的注册基础设施的需求。本文分析了五种主流方案:(1) MCP注册中心(集中式发布mcp.json描述符),(2) A2A Agent Cards(去中心化自描述JSON能力清单),(3) AGNTCY Agent目录服务(基于IPFS Kademlia DHT内容路由扩展,支持基于语义分类的内容发现、OCI工件存储及Sigstore完整性验证),(4) Microsoft Entra Agent ID(集成策略与零信任机制的企业级SaaS目录),以及(5) NANDA Index AgentFacts(采用加密可验证、保护隐私的事实模型及凭据化声明)。通过安全、认证、可扩展性和可维护性四个评估维度,我们揭示了中心化控制、企业治理与分布式韧性之间的架构权衡。最后,我们为新兴的AI智能体互联网提出了设计建议,强调其需要可验证身份、自适应发现流程及可互操作的能力语义。