A survey of agent interoperability protocols: Model Context Protocol (MCP), Agent Communication Protocol (ACP), Agent-to-Agent Protocol (A2A), and Agent Network Protocol (ANP) (2505.02279v2)

Abstract: LLM powered autonomous agents demand robust, standardized protocols to integrate tools, share contextual data, and coordinate tasks across heterogeneous systems. Ad-hoc integrations are difficult to scale, secure, and generalize across domains. This survey examines four emerging agent communication protocols: Model Context Protocol (MCP), Agent Communication Protocol (ACP), Agent-to-Agent Protocol (A2A), and Agent Network Protocol (ANP), each addressing interoperability in deployment contexts. MCP provides a JSON-RPC client-server interface for secure tool invocation and typed data exchange. ACP defines a general-purpose communication protocol over RESTful HTTP, supporting MIME-typed multipart messages and synchronous and asynchronous interactions. Its lightweight and runtime-independent design enables scalable agent invocation, while features like session management, message routing, and integration with role-based and decentralized identifiers (DIDs). A2A enables peer-to-peer task delegation using capability-based Agent Cards, supporting secure and scalable collaboration across enterprise agent workflows. ANP supports open network agent discovery and secure collaboration using W3C decentralized identifiers DIDs and JSON-LD graphs. The protocols are compared across multiple dimensions, including interaction modes, discovery mechanisms, communication patterns, and security models. Based on the comparative analysis, a phased adoption roadmap is proposed: beginning with MCP for tool access, followed by ACP for structured, multimodal messaging session-aware interaction and both online and offline agent discovery across scalable, HTTP-based deployments A2A for collaborative task execution, and extending to ANP for decentralized agent marketplaces. This work provides a comprehensive foundation for designing secure, interoperable, and scalable ecosystems of LLM-powered agents.

An Overview of Agent Interoperability Protocols for LLM-Powered Autonomous Agents

The paper "A Survey of Agent Interoperability Protocols: Model Context Protocol (MCP), Agent Communication Protocol (ACP), Agent-to-Agent Protocol (A2A), and Agent Network Protocol (ANP)" presents a comprehensive examination of emerging protocols designed to facilitate reliable and standardized communication among LLM-powered autonomous agents. The authors dissect the nuances of four distinct protocols—MCP, ACP, A2A, and ANP—each addressing specific interoperability challenges in varied deployment contexts.

Key Features and Comparative Analysis

• Model Context Protocol (MCP): MCP leverages a JSON-RPC client-server architecture to manage secure context ingestion and structured tool invocation. Its design is beneficial for integration with external resources, supporting the modular use of diverse tools.
• Agent Communication Protocol (ACP): ACP introduces REST-native performative messaging to enable asynchronous, multimodal interactions. It offers a flexible task schema and streaming capabilities, which are critical for comprehensive agent dialogue.
• Agent-to-Agent Protocol (A2A): A peer-to-peer framework, A2A enables direct task outsourcing among agents using capability-based Agent Cards. This protocol is particularly suited for enterprise-scale workflows, facilitating dynamic negotiation and collaborative task execution.
• Agent Network Protocol (ANP): ANP operates within open networks, leveraging decentralized identifiers (DIDs) and JSON-LD graphs for agent discovery and secure collaboration. It supports cross-platform interoperability and is designed for decentralized agent marketplaces.

The paper provides a detailed architectural analysis of each protocol, focusing on aspects such as communication patterns, security models, and integration strategies. A comparison highlights their interaction modes, discovery mechanisms, and security frameworks, ultimately guiding users on how to sequence their adoption effectively.

Implications and Future Directions

The discussed protocols collectively offer a robust foundation for creating modular, reusable, and resilient ecosystems of LLM-powered agents. They address pressing interoperability challenges by enabling seamless agent collaboration across diverse tools and platforms while maintaining security integrity.

The phased adoption roadmap proposed by the authors begins with MCP for tool invocation, proceeds to ACP for richer multimodal messaging, advances to A2A for collaborative enterprise workflows, and culminates with ANP for decentralized agent marketplaces. Each phase introduces capabilities that can be incrementally integrated into agent ecosystems, thereby minimizing complexity and maximizing operational efficiency.

In terms of future directions, the paper suggests the exploration of interoperability bridges among protocols to further enhance connectivity. The importance of establishing unified standards for capability negotiation and secure collaboration, alongside standardized evaluation benchmarks, is emphasized. These efforts are pivotal for advancing secure, scalable, and intelligent agent networks across various industry sectors.

Conclusion

Overall, this paper offers a rigorous exploration of the current landscape of interoperability protocols crucial for LLM-driven autonomous agents. By systematically analyzing the strengths and limitations of MCP, ACP, A2A, and ANP, the authors provide significant insights into strategic deployment and future enhancements necessary to address evolving complexities in agent communication and collaboration. As these protocols continue to develop, they promise to unlock new potentials for autonomous system design, fostering a more interconnected and efficient digital ecosystem.