The Natural Language Interaction Protocol and Standard for AI Agents
2026-09-03 • Artificial Intelligence
Artificial Intelligence
AI summaryⓘ
The authors explain that AI agents often use different systems and ways to communicate, which makes it hard for them to work together. To fix this, they helped create the Natural Language Interaction Protocol (NLIP), a standard way for AI agents to talk to each other clearly and easily. NLIP works like a simple message format that can run over common internet tools, letting different AI systems connect and share information. The paper describes how NLIP was designed, its key features, security ideas, and how it compares to similar protocols.
AI agentscommunication protocolNatural Language Interaction Protocolsemantic messagingHTTPWebSocketAMQPinteroperabilitysecurity-by-designsoftware standards
Authors
Luyi Xing, Rasit Onur Topaloglu, Ranjan Sinha, Abhay Ratnaparkhi, Samuel Ndichu, Christopher Nguyen, Anindita Das, Tom Sheffler, Mohamed Rahouti, Zichuan Li, Xiaojing Liao, Sanjay Aiyagari
Abstract
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.