A2H: Agent-to-Human Protocol for AI Agent

TL;DR

The paper introduces the A2H protocol, enabling AI agents to discover, communicate, and collaborate with humans across diverse messaging platforms, thus integrating humans into multi-agent systems.

Contribution

It proposes a standardized protocol with components for human registration, communication schemas, and messaging abstraction, facilitating human-agent interaction within AI ecosystems.

Findings

A2H enables human discovery via resolvable domain names.

The protocol standardizes communication across multiple media.

It transforms complex outputs into human-friendly formats.

Abstract

AI agents are increasingly deployed as autonomous systems capable of planning, tool use, and multi-agent collaboration across complex tasks. However, existing agent-related protocols focus on agent-to-agent interactions, leaving humans as external observers rather than integrated participants within the agent systems. This limitation arises from the lack of a standardized mechanism for agents to discover, address, and interact with humans across heterogeneous messaging platforms. In this paper, we propose the A2H (Agent-to-Human) protocol, a unified protocol that enables humans to be registered, discovered, and communicated with by AI agents as resolvable entities within agent systems. A2H contributes three key components: (1) Human Card for registering human identities via resolvable domain names, making them discoverable to agents; (2) Formal Communication Schema defines when, why, and how agents contact with human;(3) Unified Messaging Abstraction standardizes diverse communication medias and transforms complex JSON outputs into human-friendly formats. This work establishes a foundational protocol for integrating humans into agent ecosystems, advancing AI agents from isolated autonomous systems toward truly human-connected intelligent infrastructures.