mlsanityData to 14 Oct 2026

The Natural Language Interaction Protocol and Standard for AI Agents

arXiv 2609.04135 ↗First posted 3 Sep 2026cs.AIcited by 1

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Abstract (arXiv)

AI agents are increasingly being developed and deployed across organizations using heterogeneous agent-development frameworks, AI models, tool interfaces, protocols, and execution environments. To realize their potential social and business impact, these agents must be able to interoperate through a common communication protocol. The Natural Language Interaction Protocol (NLIP), developed by researchers and practitioners across companies and universities and standardized by Ecma International, addresses this need by defining a standards-based application-layer protocol for AI-agent interaction. NLIP provides a lightweight semantic message envelope that can be carried over existing transports such as HTTP/HTTPS, WebSocket, and AMQP, while allowing NLIP-aware agents and gateways to adapt between clients, agents, local context stores, ontologies, tools, enterprise services, and heterogeneous underlying protocols. This paper presents the motivation and design rationale of NLIP, its message model and transport bindings, security-by-design considerations, reference implementation, representative applications, adoption signals, and relationship to emerging agent protocols such as MCP and A2A.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 8 of its 30 references that are in the map. First posted on arXiv 3 Sep 2026.

Builds on

8 of 30 references.

References · 8

  1. 2024AgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge Basescited by 429
  2. 2024PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Modelscited by 267
  3. 2024Machine Against the RAG: Jamming Retrieval-Augmented Generation with Blocker Documentscited by 102
  4. 2025OverThink: Slowdown Attacks on Reasoning LLMscited by 96
  5. 2025Leaky Thoughts: Large Reasoning Models Are Not Private Thinkerscited by 28
  6. 2025Agent Network Protocol Technical White Papercited by 25
  7. 2024ConfusedPilot: Confused Deputy Risks in RAG-based LLMscited by 22
  8. 2025MIST: Jailbreaking Black-box Large Language Models via Iterative Semantic Tuningcited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

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  1. 2025A Survey of AI Agent Protocols
  2. 2026Beyond Message Passing: A Semantic View of Agent Communication Protocols
  3. 2024Conversational AI Multi-Agent Interoperability, Universal Open APIs for Agentic Natural Language Multimodal Communications
  4. 2025From Glue-Code to Protocols: A Critical Analysis of A2A and MCP Integration for Scalable Agent Systems
  5. 2025A Layered Protocol Architecture for the Internet of Agents
  6. 2025ACPs: Agent Collaboration Protocols for the Internet of Agents
  7. 2026Security Threat Modeling for Emerging AI-Agent Protocols: A Comparative Analysis of MCP, A2A, Agora, and ANP
  8. 2024Towards Effective GenAI Multi-Agent Collaboration: Design and Evaluation for Enterprise Applications