A2A vs MCP Protocol Relationship: In-Depth Community Discussion Analysis

🎯 Key Takeaways (TL;DR)

• Origin of Discussion: Developer questioned the relationship between A2A and MCP after seeing MCP used for agent-to-agent communication at MCP Dev Days
• Community Consensus: MCP focuses on tool standardization, A2A focuses on agent-to-agent communication - solving different layers of problems
• Core Difference: MCP is "standardization of tools," A2A is "standardization of agent collaboration"
• Ecosystem Status: MCP has more available servers, A2A has better design but lacks practical agent implementations
• Future Outlook: Both protocols may complement each other rather than compete directly

Table of Contents

1. Discussion Background
2. Community Expert Perspectives
3. Essential Differences Between MCP and A2A
4. Developer Practical Experience
5. Frequently Asked Questions

Discussion Background

This discussion originated from a developer's questions after watching the MCP Dev Days session (Microsoft Reactor event), where an agent-to-agent solution was presented using Model Context Protocol (MCP) instead of A2A.

💡 Starting Point "This raises some questions: How do A2A and MCP relate in the context of agent-to-agent communication? Are both communities working on solving the same problem?"

Core Questions Raised

• How do A2A and MCP relate in the context of agent-to-agent communication?
• Are both communities (A2A and MCP) working on solving the same problem?
• Do I need both frameworks, or are they merging at some point?
• Or is this more of a "friendly competition" between two different approaches?

Community Expert Perspectives

Perspective 1: Evolution of Tool Standardization

A community expert provided detailed explanation of the evolution from "Tools" concept to MCP standardization:

Origin of Tool Calling

User asks: "What is the price of bitcoin today"
LLM reasons: "Hmmm, I should look this up on the internet. Oh, I have the search_internet tool I can use! Let me call that"

Need for Standardization

⚠️ Early Problems "But here's where it got messy: no standardisation. Everyone was reinventing the wheel, with Tools tightly coupled to specific codebases. Very little reusability and agreed approaches to communication protocols, auth etc."

MCP's Solution

MCP defines:

• Transport protocols (initially stdio and SSE, now streaming HTTP)
• Authentication patterns
• Message formats

✅ MCP's Value "This standardisation is what made MCP take off. Suddenly, 'Tools' became reusable, plug-and-play components - like USB for AI."

Perspective 2: A2A Addresses Different Layer Problems

The same expert pointed out that A2A tackles completely different challenges:

A2A's Focus Areas:

• How autonomous agents communicate with each other
• How do they discover peers?
• Advertise capabilities?
• Handle async operations?

Specific Problems A2A Addresses:

• Service discovery
• Capability negotiation
• Streaming bidirectional communication
• Webhook patterns for long-running tasks
• Message routing

💡 Core Difference Summary

• MCP standardizes how agents use tools (making them shareable and reusable)
• A2A standardizes how agents talk to each other
• MCP is about agent-to-tool interaction; A2A is about agent-to-agent collaboration

Perspective 3: Technical Essence Reflection

Another participant offered deeper technical insights:

🤔 Technical Essence "This is where things start to feel somewhat superfluous. At their core, we're really just talking about collections of APIs, network protocols, persistence mechanisms, queues, caching layers, and so on - prior art grouped together and labeled as 'Agentic'."

Key Insights:

• Essentially, they remain what they are: APIs with supporting infrastructure
• To manage state, persistence, communication, etc.
• To interact with the large language model, the "real meat of the bones magic maker"

Essential Differences Between MCP and A2A

Design Philosophy Differences

Based on community discussion, a deeply involved participant summarized the fundamental differences:

Mechanistic vs Semantic Interoperability

MCP's Mechanistic Interoperability:

• Focuses on structured input/output schemas
• LLM responsible for generating inputs conforming to schema
• Standardizes how tools expose their capabilities structurally

A2A's Semantic Interoperability:

• Focuses on aligning agent intents
• Uses concepts like AgentCard, AgentSkill
• Declarative capability discovery
• Establishes shared semantic substrate

✅ Long-term Perspective "If we assume that agents will increasingly be asked to perform open-ended tasks under trust boundaries, then I believe the A2A framing — with its emphasis on meaning, delegation, and intent — provides a more direct foundation for agent-to-agent coordination."

Developer Practical Experience

Real Development Experience Comparison

A participant with hands-on development experience shared comparative observations:

MCP Development Experience:

• Developed several MCP servers
• Relatively mature ecosystem
• Many available MCP servers

A2A Assessment:

• Read a lot of articles about A2A
• Believes A2A is better design from architecture to implementation
• But currently no working agent implementations

⚠️ Timing Issue "Overall, I think A2A is a better design... However, right now there are many available MCP servers, while A2A doesn't yet have a working agent — this is really a matter of timing. As a result, the MCP ecosystem is much larger than A2A's."

General-Purpose Agent Challenge

An important point raised in the discussion:

General-Purpose Agent Questions:

• If general-purpose agents do work, then MCP is already sufficient
• Claude code's subagents implementation takes a general-purpose agent approach
• All it needs is a custom system prompt and an independent runtime environment
• There's no need for a truly independent agent

Reasoning:

• Everything shares the same codebase context
• Starting from chatbots, the hottest use case right now is AI coding
• What's next? Will it be multi-agent applications?

Architectural Choice Considerations

When to Choose MCP

Based on discussion content, MCP is suitable for:

• Scenarios requiring standardized tool calls
• When tools need to be reusable and plug-and-play
• Agents primarily interacting with external tools
• Leveraging existing rich MCP ecosystem

When to Consider A2A

A2A is more suitable for:

• Complex agent-to-agent collaboration needs
• Handling open-ended tasks and intent negotiation
• Agent communication across trust boundaries
• Long-term semantic alignment requirements

Hybrid Usage Possibility

💡 Practical Advice The discussion suggests that in real applications, the two are not mutually exclusive. Consider using both in the same system:

• Use MCP for standardized tool calls
• Use A2A for high-level agent collaboration

🤔 Frequently Asked Questions

Q: Are A2A and MCP solving the same problem?

A: According to community discussion, no. MCP focuses on standardizing agent-tool interactions, while A2A focuses on standardizing agent-agent communication. They solve problems at different layers.

Q: Why is the MCP ecosystem larger than A2A's?

A: It's mainly a matter of timing. MCP already has many available server implementations, while A2A, though better designed, still lacks working agent implementations.

Q: Will the two protocols merge?

A: Based on the discussion, it's more likely that they will complement each other in different scenarios rather than merge directly. They solve different core problems.

Q: How to choose which protocol to use?

A: According to discussion suggestions:

• If the main need is tool standardization and reuse, choose MCP
• If complex agent-to-agent collaboration and semantic alignment are needed, consider A2A
• In complex systems, both may need to be used in combination

Summary and Outlook

Community Consensus

Based on this in-depth discussion, the main community consensus on the A2A and MCP relationship includes:

1. Different Layer Problems: Both solve standardization needs at different layers of AI systems
2. Complementary Not Competitive: More likely to be complementary rather than directly competitive
3. Different Development Stages: MCP ecosystem is more mature, A2A theory is more complete
4. Choice Based on Needs: Should choose appropriate protocol based on specific application scenarios

Future Development Directions

Trends suggested by the discussion:

• MCP will continue developing in tool standardization
• A2A needs more practical implementations to validate its design concepts
• Higher-level abstractions combining advantages of both may emerge
• Multi-agent applications may become the next hot area

✅ Practical Advice For developers, understanding the essential differences between the two is more important than choosing the "correct" protocol. In actual projects, flexible use or combination of these protocols may be needed based on specific requirements.

This article is compiled from real developer discussions in the A2A project discussion area on GitHub, reflecting the community's deep thinking and practical experience regarding the relationship between these two protocols.