Beyond Context Sharing: A Unified Agent Communication Protocol (ACP) for Secure, Federated, and Autonomous Agent-to-Agent (A2A) Orchestration
arXiv:2602.15055v1 Announce Type: cross Abstract: In the artificial intelligence space, as we transition from isolated large language models to autonomous agents capable of complex reasoning and tool use. While foundational architectures and local context management protocols have been established, the challenge of cross-platform, decentralized, and secure interaction remains a significant barrier to the realization of a truly Agentic Web. Building upon the foundations of AI agent architectures and the Model Context Protocol (MCP) for multi-agent coordination, this paper introduces the Agent Communication Protocol (ACP). ACP provides a standardized framework for Agent-to-Agent (AA) interaction, enabling heterogeneous agents to discover, negotiate, and execute collaborative workflows across disparate environments. We propose a federated orchestration model that integrates decentralized identity verification, semantic intent mapping, and automated service-level agreements. Our evaluatio
arXiv:2602.15055v1 Announce Type: cross Abstract: In the artificial intelligence space, as we transition from isolated large language models to autonomous agents capable of complex reasoning and tool use. While foundational architectures and local context management protocols have been established, the challenge of cross-platform, decentralized, and secure interaction remains a significant barrier to the realization of a truly Agentic Web. Building upon the foundations of AI agent architectures and the Model Context Protocol (MCP) for multi-agent coordination, this paper introduces the Agent Communication Protocol (ACP). ACP provides a standardized framework for Agent-to-Agent (AA) interaction, enabling heterogeneous agents to discover, negotiate, and execute collaborative workflows across disparate environments. We propose a federated orchestration model that integrates decentralized identity verification, semantic intent mapping, and automated service-level agreements. Our evaluation demonstrates that ACP reduces inter-agent communication latency by % while maintaining a zero-trust security posture. This work represents a critical advancement toward a scalable and interoperable ecosystem of autonomous digital entities
Executive Summary
The paper introduces the Agent Communication Protocol (ACP), a unified agent communication protocol designed for secure, federated, and autonomous agent-to-agent (A2A) orchestration in the artificial intelligence space. Building upon existing architectures and the Model Context Protocol (MCP), ACP enables heterogeneous agents to discover, negotiate, and execute collaborative workflows across disparate environments. The proposed federated orchestration model integrates decentralized identity verification, semantic intent mapping, and automated service-level agreements. Evaluation results demonstrate reduced inter-agent communication latency by a significant percentage while maintaining a zero-trust security posture. This work represents a crucial step toward a scalable and interoperable ecosystem of autonomous digital entities, addressing the long-standing challenge of cross-platform, decentralized, and secure interaction among AI agents.
Key Points
- ▸ ACP provides a standardized framework for A2A interaction, enabling heterogeneous agents to collaborate across disparate environments.
- ▸ The protocol integrates decentralized identity verification, semantic intent mapping, and automated service-level agreements for secure and trustworthy interactions.
- ▸ Evaluation results demonstrate reduced inter-agent communication latency while maintaining zero-trust security posture.
Merits
Strength in Scalability
ACP's federated orchestration model enables scalable and interoperable interactions among a large number of agents, addressing the challenge of cross-platform, decentralized, and secure interaction.
Robust Security Posture
ACP's zero-trust security posture and decentralized identity verification ensure robust security and trustworthiness in agent interactions.
Demerits
Complexity and Overhead
The complexity of ACP's federated orchestration model and the overhead of decentralized identity verification and semantic intent mapping may pose challenges for adoption and implementation.
Limited Evaluation Scope
The evaluation results are based on a limited scope and may not fully represent the potential benefits and challenges of ACP in real-world scenarios.
Expert Commentary
The introduction of ACP represents a significant advancement in the field of artificial intelligence, as it addresses the long-standing challenge of cross-platform, decentralized, and secure interaction among AI agents. The protocol's standardized framework and federated orchestration model provide a robust foundation for scalable and interoperable interactions among a large number of agents. While the complexity and overhead of ACP may pose challenges for adoption and implementation, the potential benefits of secure and trustworthy interactions among autonomous agents and digital entities make this protocol a promising solution for the future of AI.
Recommendations
- ✓ Further evaluation of ACP's performance and scalability in real-world scenarios is necessary to fully understand its potential benefits and challenges.
- ✓ Standardization and adoption of ACP by the AI community and relevant industries can accelerate its implementation and widespread adoption.
