From Glue-Code to Protocols: A Critical Analysis of A2A and MCP Integration for Scalable Agent Systems
Qiaomu Li, Ying Xie·May 06, 2025
Summary
The paper examines the integration of Google's A2A protocol and Anthropic's MCP in multi-agent systems, highlighting challenges like semantic interoperability, security risks, and governance. It assesses the practical implications of combining these standards, noting increased security vulnerabilities, privacy complexities, and debugging difficulties. The text also discusses advancements in multi-agent systems, focusing on topics like Vertex AI capabilities, security risks, governance, planning, privacy, and AI agent evolution. It explores areas such as context-aware systems, agent communication languages, bot integration in supply chains, proof assistant verification, and multi-agent security. The paper also delves into agent-based computational economics and AI agent development trends.
Introduction
Background
Overview of Google's A2A protocol and Anthropic's MCP
Objective
To examine the integration of Google's A2A protocol and Anthropic's MCP in multi-agent systems, focusing on challenges and practical implications
Challenges in Integration
Semantic Interoperability
Issues in understanding and translating data across different systems
Security Risks
Increased vulnerabilities due to the integration of multiple protocols
Governance
Complexities in managing and regulating the interaction between systems
Practical Implications
Security Vulnerabilities
Detailed analysis of potential security breaches and countermeasures
Privacy Complexities
Examination of privacy concerns and data protection strategies
Debugging Difficulties
Strategies for identifying and resolving integration issues
Advancements in Multi-Agent Systems
Vertex AI Capabilities
Overview of AI capabilities in multi-agent systems
Security Risks
Discussion on evolving security threats and counter strategies
Governance
Best practices for governance in multi-agent systems
Planning
Techniques for effective planning in complex multi-agent environments
Privacy
Strategies for maintaining privacy in multi-agent interactions
AI Agent Evolution
Trends in AI agent development and their integration into multi-agent systems
Specific Topics
Context-Aware Systems
Importance and implementation of context-awareness in multi-agent systems
Agent Communication Languages
Overview of communication protocols and their role in multi-agent systems
Bot Integration in Supply Chains
Case studies on integrating bots in supply chain management
Proof Assistant Verification
Use of proof assistants in ensuring the reliability of multi-agent systems
Multi-Agent Security
Comprehensive security measures for protecting multi-agent systems
Agent-Based Computational Economics
Overview of agent-based models in economics
AI Agent Development Trends
Current trends and future directions in AI agent development
Conclusion
Summary of findings
Recommendations for future research
Basic info
papers
machine learning
artificial intelligence
multiagent systems
Advanced features
Insights
How do Google's A2A protocol and Anthropic's MCP integrate within multi-agent systems?
What are the practical implications of combining A2A and MCP standards in terms of security and privacy?
What are the key challenges in implementing semantic interoperability and security in multi-agent systems?
What advancements in multi-agent systems are highlighted in the paper, particularly regarding AI agent evolution and context-aware systems?