Beyond DNS: Unlocking the Internet of AI Agents via the NANDA Index and Verified AgentFacts
- URL: http://arxiv.org/abs/2507.14263v1
- Date: Fri, 18 Jul 2025 13:40:46 GMT
- Title: Beyond DNS: Unlocking the Internet of AI Agents via the NANDA Index and Verified AgentFacts
- Abstract summary: We describe the NANDA index architecture, which we envision as a means for discoverability, identifiability and authentication in the internet of AI agents.<n>We present an architecture where a minimal lean index resolves to dynamic, cryptographically verifiable AgentFacts.
- Score: 12.955380032776068
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The Internet is poised to host billions to trillions of autonomous AI agents that negotiate, delegate, and migrate in milliseconds and workloads that will strain DNS-centred identity and discovery. In this paper, we describe the NANDA index architecture, which we envision as a means for discoverability, identifiability and authentication in the internet of AI agents. We present an architecture where a minimal lean index resolves to dynamic, cryptographically verifiable AgentFacts that supports multi-endpoint routing, load balancing, privacy-preserving access, and credentialed capability assertions. Our architecture design delivers five concrete guarantees: (1) A quilt-like index proposal that supports both NANDA-native agents as well as third party agents being discoverable via the index, (2) rapid global resolution for newly spawned AI agents, (3) sub-second revocation and key rotation, (4) schema-validated capability assertions, and (5) privacy-preserving discovery across organisational boundaries via verifiable, least-disclosure queries. We formalize the AgentFacts schema, specify a CRDT-based update protocol, and prototype adaptive resolvers. The result is a lightweight, horizontally scalable foundation that unlocks secure, trust-aware collaboration for the next generation of the Internet of AI agents, without abandoning existing web infrastructure.
Related papers
- DecodingTrust-Agent Platform (DTap): A Controllable and Interactive Red-Teaming Platform for AI Agents [121.77550256034]
DecodingTrust-Agent Platform (DTap) is a controllable and interactive red-teaming platform for AI agents.<n>DTap-Red is the first autonomous red-teaming agent that explores diverse injection vectors and autonomously discovers effective attack strategies.<n>Through DTap, we conduct large-scale evaluations of popular AI agents built on various backbone models.
arXiv Detail & Related papers (2026-05-06T11:59:48Z) - Agent Name Service (ANS): A Proof-of-Concept Trust Layer for Secure AI Agent Discovery, Identity, and Governance in Kubernetes [0.0]
This paper presents an implementation-oriented proof of concept for the Agent Name Service (ANS)<n>ANS is a DNS-inspired trust layer for AI agent discovery and interoperability.<n>We observe sub-10ms response in demonstrated service paths and full success for scripted demo deployment scenarios.
arXiv Detail & Related papers (2026-04-29T01:24:27Z) - Federated Agentic AI for Wireless Networks: Fundamentals, Approaches, and Applications [60.721304295812445]
Federated learning (FL) has the potential to improve the overall loop of agentic AI.<n>We first summarize fundamentals of agentic AI and mainstream FL types. Then, we illustrate how each FL type can strengthen a specific component of agentic AI's loop.<n>We conduct a case study on using FRL to improve the performance of agentic AI's action decision in low-altitude wireless networks.
arXiv Detail & Related papers (2026-03-02T11:26:56Z) - Agent Identity URI Scheme: Topology-Independent Naming and Capability-Based Discovery for Multi-Agent Systems [0.0]
Multi-agent systems face a fundamental architectural flaw: agent identity is bound to network location.<n>We propose the agent:// scheme, which decouples identity from topology through three components.<n>Trust root establishing organizational authority, a hierarchical capability path, and a sortable unique identifier provide stable reference.
arXiv Detail & Related papers (2026-01-21T01:09:22Z) - AgentRouter: A Knowledge-Graph-Guided LLM Router for Collaborative Multi-Agent Question Answering [51.07491603393163]
tAgent is a framework that formulates multi-agent QA as a knowledge-graph-guided routing problem supervised by empirical performance signals.<n>By leveraging soft supervision and weighted aggregation of agent outputs, Agent learns principled collaboration schemes that capture the complementary strengths of diverse agents.
arXiv Detail & Related papers (2025-10-06T23:20:49Z) - Using the NANDA Index Architecture in Practice: An Enterprise Perspective [9.707223291705601]
The proliferation of autonomous AI agents represents a paradigmatic shift from traditional web architectures toward collaborative intelligent systems.<n>This paper presents a comprehensive framework addressing the fundamental infrastructure requirements for secure, trustworthy, and interoperable AI agent ecosystems.
arXiv Detail & Related papers (2025-08-05T05:27:27Z) - A Survey of AI Agent Registry Solutions [10.500986125166454]
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.
arXiv Detail & Related papers (2025-08-05T05:17:18Z) - Cognitive Kernel-Pro: A Framework for Deep Research Agents and Agent Foundation Models Training [67.895981259683]
General AI Agents are increasingly recognized as foundational frameworks for the next generation of artificial intelligence.<n>Current agent systems are either closed-source or heavily reliant on a variety of paid APIs and proprietary tools.<n>We present Cognitive Kernel-Pro, a fully open-source and (to the maximum extent) free multi-module agent framework.
arXiv Detail & Related papers (2025-08-01T08:11:31Z) - Agentic Web: Weaving the Next Web with AI Agents [109.13815627467514]
The emergence of AI agents powered by large language models (LLMs) marks a pivotal shift toward the Agentic Web.<n>In this paradigm, agents interact directly with one another to plan, coordinate, and execute complex tasks on behalf of users.<n>We present a structured framework for understanding and building the Agentic Web.
arXiv Detail & Related papers (2025-07-28T17:58:12Z) - Upgrade or Switch: Do We Need a Next-Gen Trusted Architecture for the Internet of AI Agents? [12.116270471408216]
The emerging Internet of AI Agents challenges existing web infrastructure designed for human-scale, reactive interactions.<n>This paper analyzes whether to upgrade existing infrastructure or implement purpose-built index architectures for autonomous agents.
arXiv Detail & Related papers (2025-06-13T17:55:38Z) - WebCoT: Enhancing Web Agent Reasoning by Reconstructing Chain-of-Thought in Reflection, Branching, and Rollback [74.82886755416949]
We identify key reasoning skills essential for effective web agents.<n>We reconstruct the agent's reasoning algorithms into chain-of-thought rationales.<n>Our approach yields significant improvements across multiple benchmarks.
arXiv Detail & Related papers (2025-05-26T14:03:37Z) - A Novel Zero-Trust Identity Framework for Agentic AI: Decentralized Authentication and Fine-Grained Access Control [7.228060525494563]
This paper posits the imperative for a novel Agentic AI IAM framework.<n>We propose a comprehensive framework built upon rich, verifiable Agent Identities (IDs)<n>We also explore how Zero-Knowledge Proofs (ZKPs) enable privacy-preserving attribute disclosure and verifiable policy compliance.
arXiv Detail & Related papers (2025-05-25T20:21:55Z) - Agent Name Service (ANS): A Universal Directory for Secure AI Agent Discovery and Interoperability [0.0]
The proliferation of AI agents requires robust mechanisms for secure discovery.<n>This paper introduces the Agent Name Service (ANS), a novel architecture based on DNS addressing the lack of a public agent discovery framework.
arXiv Detail & Related papers (2025-05-15T17:49:36Z) - Internet of Agents: Fundamentals, Applications, and Challenges [66.44234034282421]
We introduce the Internet of Agents (IoA) as a foundational framework that enables seamless interconnection, dynamic discovery, and collaborative orchestration among heterogeneous agents at scale.<n>We analyze the key operational enablers of IoA, including capability notification and discovery, adaptive communication protocols, dynamic task matching, consensus and conflict-resolution mechanisms, and incentive models.
arXiv Detail & Related papers (2025-05-12T02:04:37Z) - AgentVigil: Generic Black-Box Red-teaming for Indirect Prompt Injection against LLM Agents [54.29555239363013]
We propose a generic black-box fuzzing framework, AgentVigil, to automatically discover and exploit indirect prompt injection vulnerabilities.<n>We evaluate AgentVigil on two public benchmarks, AgentDojo and VWA-adv, where it achieves 71% and 70% success rates against agents based on o3-mini and GPT-4o.<n>We apply our attacks in real-world environments, successfully misleading agents to navigate to arbitrary URLs, including malicious sites.
arXiv Detail & Related papers (2025-05-09T07:40:17Z) - Internet of Agents: Weaving a Web of Heterogeneous Agents for Collaborative Intelligence [79.5316642687565]
Existing multi-agent frameworks often struggle with integrating diverse capable third-party agents.
We propose the Internet of Agents (IoA), a novel framework that addresses these limitations.
IoA introduces an agent integration protocol, an instant-messaging-like architecture design, and dynamic mechanisms for agent teaming and conversation flow control.
arXiv Detail & Related papers (2024-07-09T17:33:24Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.