A2A Protocol vs MCP vs Amorce: Which AI Agent Protocol Should You Use?

The AI agent ecosystem is maturing rapidly. Google announced the A2A Protocol, Anthropic introduced MCP (Model Context Protocol), and Amorce provides the AATP (Amorce Agent Transmission Protocol). But which one should you use?

This guide compares all three protocols to help you make the right choice for your AI agent architecture.

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The Problem: AI Agents Can't Talk to Each Other

Here's the reality of building AI agents today:

• Your LangChain agent can't call a CrewAI crew
• Your n8n workflow can't discover a AutoGPT agent
• ChatGPT can't find your custom agent

Each framework operates in isolation. Building integrations means writing custom API code, handling authentication, and hoping the other side doesn't change their interface.

The solution? Agent communication protocols.

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What is Google's A2A Protocol?

A2A (Agent-to-Agent) Protocol is Google's standard for agent communication.

Key Features

• JSON-RPC based — Standardized message format
• Agent Cards — Metadata describing agent capabilities
• Task-based — Agents exchange task requests and results

When to Use A2A

• Building agents in the Google Cloud ecosystem
• Need standardized message formats for enterprise compliance
• Working with Google's Agent Builder platform

Limitations

• No built-in security — No cryptographic signatures
• Google-centric — Primary focus on Google Cloud integration
• Early stage — Still evolving, limited adoption

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What is Anthropic's MCP (Model Context Protocol)?

MCP (Model Context Protocol) is Anthropic's standard for connecting LLMs to external tools.

Key Features

• Tool discovery — LLMs can find and use external tools
• Resource access — Structured way to provide context to models
• Claude integration — Native support in Claude Desktop and API

When to Use MCP

• Building tools for Claude specifically
• Need LLM-to-tool communication (not agent-to-agent)
• Want plug-and-play tool discovery

Limitations

• Tool-focused, not agent-focused — Designed for LLM→Tool, not Agent→Agent
• No cross-framework support — Doesn't help LangChain talk to CrewAI
• No human-in-the-loop — No built-in approval workflows

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What is Amorce AATP?

Amorce AATP (Amorce Agent Transmission Protocol) is the universal trust layer for AI agent communication.

Key Features

• Cross-framework — LangChain, CrewAI, n8n, AutoGPT all connected
• Ed25519 signatures — Every message cryptographically signed
• Human-in-the-loop — Built-in approval workflows for sensitive actions
• LLM discovery — ChatGPT, Claude, Gemini can find your agents via MCP
• 5-minute integration — Simple SDK for Python and JavaScript

When to Use Amorce

• Need cross-framework agent communication
• Building agents that call other agents (not just tools)
• Require cryptographic security and audit trails
• Want any LLM to discover your agent

Why Amorce is Different

Amorce doesn't replace A2A or MCP — it complements them. You can:

• Use MCP for tool discovery, with Amorce signatures
• Format messages as A2A, verified by Amorce

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Side-by-Side Comparison

Feature	A2A Protocol	MCP	Amorce AATP
Primary Use	Agent cards & tasks	LLM → Tool discovery	Agent → Agent trust
Security	❌ None built-in	❌ None built-in	✅ Ed25519 signatures
Cross-Framework	❌ Google-focused	❌ Tool-focused	✅ Any framework
Human-in-the-Loop	❌ No	❌ No	✅ Built-in
LLM Discovery	🔜 Planned	✅ Claude	✅ ChatGPT, Claude, Gemini
Framework Support	Google Agent Builder	Claude tools	LangChain, CrewAI, n8n, AutoGPT
Integration Time	Hours-days	Minutes	5 minutes

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Real-World Examples

Scenario 1: n8n Workflow Calls CrewAI Crew

Without Amorce:

• Write custom HTTP client
• Handle authentication manually
• No verification of response authenticity

With Amorce:

text
n8n → [Signed Request] → Amorce → [Verified] → CrewAI

Scenario 2: ChatGPT Finds Your Travel Agent

Without Amorce:

• Build custom ChatGPT plugin
• Host OpenAPI spec
• No discoverability standard

With Amorce:

javascript
// Your agent is registered
// ChatGPT uses MCP to discover via Amorce
// User says: "Find me a flight to Paris"
// → Your agent gets called automatically

Scenario 3: Human Approval for $5000 Booking

Without Amorce:

• Build custom approval UI
• Handle timeout logic
• No audit trail

With Amorce:

python
# Built-in HITL
approval_id = client.request_approval(
    summary="Book flight: NYC → Paris, $4,999",
    timeout_seconds=300
)
# Human reviews, approves
# Transaction proceeds with audit log

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Which Protocol Should You Choose?

Choose A2A Protocol if:

• You're building exclusively in Google Cloud
• You need Google Agent Builder integration
• You're comfortable with early-stage standards

Choose MCP if:

• You're building tools for Claude specifically
• You need LLM-to-tool connections
• You want plug-and-play tool discovery for Anthropic products

Choose Amorce AATP if:

• You need agent-to-agent communication
• You're using multiple frameworks (LangChain + CrewAI + n8n)
• You require cryptographic security
• You need human-in-the-loop approval
• You want any LLM to discover your agent

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The Future: Protocols Working Together

The best architecture often combines protocols:

text
┌─────────────────────────────────────────────────┐
│                  Your Agent                      │
├─────────────┬─────────────┬─────────────────────┤
│   A2A       │    MCP      │    Amorce AATP      │
│  (Format)   │  (Discovery)│  (Trust & Security)  │
└─────────────┴─────────────┴─────────────────────┘

Amorce is designed to work alongside other protocols, adding the security layer they're missing.

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Get Started with Amorce

Ready to connect your agents securely?

1. Install the SDK

   bash
   pip install amorce-sdk  # Python
   npm install @amorce/sdk  # JavaScript

2. Verify incoming requests (2 lines)

   python
   from amorce import verify_request
   verified = verify_request(headers, body)

3. Register your agent for discovery

   • Validate your agent →
   • Register in the directory →

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Conclusion

A2A, MCP, and Amorce each solve different problems:

• A2A = Standardized message format (Google ecosystem)
• MCP = LLM tool discovery (Claude/Anthropic)
• Amorce = Cross-framework trust layer (universal)

If you're building agents that need to talk to agents across different frameworks — with security, human oversight, and universal discoverability — Amorce is the protocol for you.

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One Trust Layer. Any Agent. Any Framework.

👉 Get started at amorce.io