These key research papers outlining the architectural, strategic, and technical foundations of the NANDA (Networked Agents and Decentralized AI) initiative at MIT Media Lab. Each document contributes uniquely to the vision of the Internet of Agents.
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Details the design of a minimal, privacy-preserving index architecture for agent discovery. Introduces the AgentFacts schema, TTL-based endpoint resolution, and cryptographic verification for agent capabilities. Offers concrete mechanisms for multi-endpoint routing, least-disclosure queries, and rapid revocation in decentralized agent ecosystems.
AdaptiveResolver is a dynamic microservice architecture designed to address the limitations of static endpoint resolution for AI agent communication in distributed, heterogeneous environments.
Analyzes the limitations of DNS and web infrastructure for AI agent systems. Weighs incremental upgrades (e.g., DNS push, SVCB records) against purpose-built registries. Offers analogies like dial-up to broadband and outlines the technical deltas introduced by the agent paradigm.
Presents the NANDA framework for secure AI agent ecosystems and cross-protocol interoperability, and explores enterprise use cases. Introduces Zero Trust Agentic Access (ZTAA) and Agent Visibility & Control (AVC) for enterprise governance of autonomous agent collaboration.
Compares leading registry architectures - MCP, A2A, Microsoft Entra Agent ID, and NANDA, across security, scalability, authentication, and maintainability. Highlights NANDA’s AgentFacts as a privacy-preserving, cryptographically verifiable schema purpose-built for dynamic, multi-agent systems.
Proposes a federated security architecture that combines NANDA’s minimal registry with the Agent Name Service (ANS) for dual-trust anchoring. Features include verifiable credentials, zero-knowledge proofs, and a modular governance system for agent discovery and capability validation.
Outlines five foundational challenges for decentralized AI systems: privacy, verifiability, incentives, orchestration, and user experience. The paper proposes a layered architectural approach and highlights parallels with internet infrastructure like TCP/IP and DNS.
Investigates the stark disparity in enterprise GenAI and Agentic AI adoption, identifying the critical gap between static tools and learning-capable systems.
Introduces the rise of intelligent agents from early LLM tooling to multi-agent systems. It discusses protocol evolution, especially the Model Context Protocol (MCP), and sets the stage for emerging agent infrastructure battles.
Explores the need for an agent registry to enable discovery, trust, and collaboration among dynamic and ephemeral AI agents. Compares governance models including platform-led, consortium-led, and decentralized blockchain-based approaches.
Presents a layered architecture for live multi-agent interaction via chat interfaces. Describes client, communication, and context agent roles with example use cases. Demonstrates real-time coordination enabled by the NANDA registry.
Identifies that we are headed toward protocol wars in agentic AI ecosystems. Proposes minimal web-based standards as a solution to enable interoperability across agents and prevent fragmentation in the ecosystem.
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