Original title: The Natural Language Interaction Protocol and Standard for AI Agents
Luyi Xing, Rasit Onur Topaloglu, Ranjan Sinha, Abhay Ratnaparkhi +8 · September 2026
Organizations build artificial intelligence agents using many different models, tools, code frameworks, and environments. Because these systems are so varied, they struggle to talk to each other and work together. To fix this, researchers and industry experts created the Natural Language Interaction Protocol, or NLIP, which is now standardized by Ecma International. NLIP gives agents a shared language. It works by wrapping communications in a lightweight message envelope that travels across existing networks like HTTP, WebSocket, or AMQP. Inside this system, smart agents and gatewaysSystems that help translate or route messages between agents, tools, or different protocols. translate between different tools, services, client programs, and background data. As a result, NLIP helps varied AI agents connect and collaborate smoothly across separate platforms and technologies.
Imagine you're at a potluck where everyone brings a dish, but each cook follows a recipe book in a different language. When you try to ask about ingredients or share tips, you can't understand each other because the instructions are all written differently. In this paper, AI agents are like these cooks, each using their own tools to prepare tasks. NLIP is like agreeing on a universal recipe card format that everyone uses, so even if the books differ, the agents can still share and understand the dishes.
AI agents are built by different teams with incompatible tools, so they can't collaborate, limiting their real-world use. NLIP lets these agents communicate across platforms, enabling them to work together on larger tasks and impact.
The abstract does not address real-world performance, scalability, or adoption rates. It focuses on design and motivation without detailing how NLIP performs in large-scale deployments or compared to alternatives in practice.
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The Natural Language Interaction Protocol and Standard for AI Agents — Luyi Xing, Rasit Onur Topaloglu, Ranjan Sinha et al.
Abstract licence: CC0
Explanation generated by Synthesis from the abstract — it is not the original paper. This is a preprint, so it hasn't necessarily been peer reviewed.