A Comparative Study of MCP and A2A for Inter-Agent Coordination in LLM-Based Systems
On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks
Abstract (arXiv)
Recent industry practice has seen the rapid emergence of agentic systems composed of heterogeneous, tool- and LLM-mediated agent components, raising practical questions about inter-agent coordination and protocol design. This paper presents an implementation-grounded comparison of the Model Context Protocol (MCP) and the Agent2Agent (A2A) protocol, from a multi-agent systems engineering perspective, using an inter-agent coordination scenario involving LLM-based agents. We evaluate an MCP-based and an A2A-based multi-agent implementation of the same software engineering task against a set of requirements derived from prior literature and discussions with industry partners, including agent discoverability, multi-part messaging, multi-turn conversations, asynchronous communication, observability, interoperability, and access control. The results evidence that MCP can support inter-agent coordination in constrained LLM-based systems through a comparatively lightweight implementation model with lower coordination complexity, although coordination concerns such as conversational state management and task lifecycle handling must be implemented explicitly at the application layer. In contrast, A2A provides richer native support for stateful, multi-turn coordination through protocol-level abstractions for tasks and lifecycle management, but this comes with substantially greater implementation and coordination complexity. Given the narrow scope of the evaluated coordination pattern, these findings are presented as design observations from an empirical experience report rather than general claims of protocol suitability or superiority across broader classes of MAS, highlighting trade-offs and how protocol abstractions shape the distribution of coordination responsibilities in contemporary agentic systems.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 9 of its 51 references that are in the map. First posted on arXiv 26 Jul 2026.
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9 of 51 references.
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- 2025AgentMaster: A Multi-Agent Conversational Framework Using A2A and MCP Protocols for Multimodal Information Retrieval and Analysis8 Jul
- 2025A Study on the MCP x A2A Framework for Enhancing Interoperability of LLM-based Autonomous Agents2 Jun
- 2025A Survey of AI Agent Protocols23 Apr
Other references · 6
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
- 2025A survey of agent interoperability protocols: Model Context Protocol (MCP), Agent Communication Protocol (ACP), Agent-to-Agent Protocol (A2A), and Agent Network Protocol (ANP)cited by 101
- 2025From Glue-Code to Protocols: A Critical Analysis of A2A and MCP Integration for Scalable Agent Systemscited by 14
- 2025Building A Secure Agentic AI Application Leveraging A2A Protocolcited by 9
- 2026Kiko: Programming Agents to Enact Interaction Protocolscited by 2
- 2026Langshaw: Declarative Interaction Protocols Based on Sayso and Conflictcited by 1
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