# From Glue-Code to Protocols: A Critical Analysis of A2A and MCP Integration for Scalable Agent Systems

arXiv: https://arxiv.org/abs/2505.03864 · HTML: https://mlsanity.com/paper/2505.03864/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- Builds on 24 of its 46 references that are in the map.
- First posted on arXiv 6 May 2025.

## Builds on (most cited first, 24 of 24)

- [The Rise and Potential of Large Language Model Based Agents: A Survey](https://mlsanity.com/paper/2309.07864/) (2023)
- [HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face](https://mlsanity.com/paper/2303.17580/) (2023)
- [ToolSandbox: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilities](https://mlsanity.com/paper/2408.04682/) (2024)
- [Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions](https://mlsanity.com/paper/2503.23278/) (2025)
- [The Emerged Security and Privacy of LLM Agent: A Survey with Case Studies](https://mlsanity.com/paper/2407.19354/) (2024)
- [AI Agents Under Threat: A Survey of Key Security Challenges and Future Pathways](https://mlsanity.com/paper/2406.02630/) (2024)
- [A Survey of AI Agent Protocols](https://mlsanity.com/paper/2504.16736/) (2025)
- [Imprompter: Tricking LLM Agents into Improper Tool Use](https://mlsanity.com/paper/2410.14923/) (2024)
- [Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents](https://mlsanity.com/paper/2411.09523/) (2024)
- [LLM With Tools: A Survey](https://mlsanity.com/paper/2409.18807/) (2024)
- [Tool Learning in the Wild: Empowering Language Models as Automatic Tool Agents](https://mlsanity.com/paper/2405.16533/) (2024)
- [LLM Agents Making Agent Tools](https://mlsanity.com/paper/2502.11705/) (2025)
- [Enterprise-Grade Security for the Model Context Protocol (MCP): Frameworks and Mitigation Strategies](https://mlsanity.com/paper/2504.08623/) (2025)
- [Multi-Agent Coordination across Diverse Applications: A Survey](https://mlsanity.com/paper/2502.14743/) (2025)
- [Agent-Oriented Planning in Multi-Agent Systems](https://mlsanity.com/paper/2410.02189/) (2024)
- [A Survey on Context-Aware Multi-Agent Systems: Techniques, Challenges and Future Directions](https://mlsanity.com/paper/2402.01968/) (2024)
- [Multi-Agent Security Tax: Trading Off Security and Collaboration Capabilities in Multi-Agent Systems](https://mlsanity.com/paper/2502.19145/) (2025)
- [AI Agents: Evolution, Architecture, and Real-World Applications](https://mlsanity.com/paper/2503.12687/) (2025)
- [ToolFuzz -- Automated Agent Tool Testing](https://mlsanity.com/paper/2503.04479/) (2025)
- [Securing GenAI Multi-Agent Systems Against Tool Squatting: A Zero Trust Registry-Based Approach](https://mlsanity.com/paper/2504.19951/) (2025)
- [Will bots take over the supply chain? Revisiting Agent-based supply chain automation](https://mlsanity.com/paper/2109.01703/) (2021)
- [Can We Govern the Agent-to-Agent Economy?](https://mlsanity.com/paper/2501.16606/) (2025)
- [Can Proof Assistants Verify Multi-Agent Systems?](https://mlsanity.com/paper/2503.06812/) (2025)
- [Multi-Agent Verification and Control with Probabilistic Model Checking](https://mlsanity.com/paper/2308.02829/) (2023)

## Built on by (most cited first, 14 of 14)

- [A Survey of Context Engineering for Large Language Models](https://mlsanity.com/paper/2507.13334/) (2025)
- [A Survey of LLM-Driven AI Agent Communication: Protocols, Security Risks, and Defense Countermeasures](https://mlsanity.com/paper/2506.19676/) (2025)
- [Agentic AI: A Comprehensive Survey of Architectures, Applications, and Future Directions](https://mlsanity.com/paper/2510.25445/) (2025)
- [Code as Agent Harness](https://mlsanity.com/paper/2605.18747/) (2026)
- [BlockA2A: Towards Secure and Verifiable Agent-to-Agent Interoperability](https://mlsanity.com/paper/2508.01332/) (2025)
- [Agentic Services Computing](https://mlsanity.com/paper/2509.24380/) (2025)
- [Formalizing the Safety, Security, and Functional Properties of Agentic AI Systems](https://mlsanity.com/paper/2510.14133/) (2025)
- [Towards Unifying Quantitative Security Benchmarking for Multi Agent Systems](https://mlsanity.com/paper/2507.21146/) (2025)
- [Agentic Semantic Control for Autonomous Wireless Space Networks: Extending Space-O-RAN with MCP-Driven Distributed Intelligence](https://mlsanity.com/paper/2506.10925/) (2025)
- [STEM Agent: A Self-Adapting, Tool-Enabled, Extensible Architecture for Multi-Protocol AI Agent Systems](https://mlsanity.com/paper/2603.22359/) (2026)
- [Execution-bound advisory automation for agentic AI: a reproducible AIBOM-driven CSAF-VEX framework](https://mlsanity.com/paper/2606.19390/) (2026)
- [A Comparative Study of MCP and A2A for Inter-Agent Coordination in LLM-Based Systems](https://mlsanity.com/paper/2607.23884/) (2026)
- [Cartograph: Federated Tool Discovery with Operator-Attested Retrieval for AI Agents](https://mlsanity.com/paper/2609.30293/) (2026)
- [Agent-Canary-Mas: End-to-End Evaluation of Protocol Risk in Long-Horizon Multi-Agent Systems](https://mlsanity.com/paper/2610.15529/) (2026)

## Abstract (arXiv)

Artificial intelligence is rapidly evolving towards multi-agent systems where numerous AI agents collaborate and interact with external tools. Two key open standards, Google's Agent to Agent (A2A) protocol for inter-agent communication and Anthropic's Model Context Protocol (MCP) for standardized tool access, promise to overcome the limitations of fragmented, custom integration approaches. While their potential synergy is significant, this paper argues that effectively integrating A2A and MCP presents unique, emergent challenges at their intersection, particularly concerning semantic interoperability between agent tasks and tool capabilities, the compounded security risks arising from combined discovery and execution, and the practical governance required for the envisioned "Agent Economy". This work provides a critical analysis, moving beyond a survey to evaluate the practical implications and inherent difficulties of combining these horizontal and vertical integration standards. We examine the benefits (e.g., specialization, scalability) while critically assessing their dependencies and trade-offs in an integrated context. We identify key challenges increased by the integration, including novel security vulnerabilities, privacy complexities, debugging difficulties across protocols, and the need for robust semantic negotiation mechanisms. In summary, A2A+MCP offers a vital architectural foundation, but fully realizing its potential requires substantial advancements to manage the complexities of their combined operation.