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A2A vs MCP: A Comprehensive Protocol Comparison

A2A vs MCP: A Comprehensive Protocol Comparison

This guide compares the Model Context Protocol (MCP) and the Agent-to-Agent (A2A) protocol, two leading protocols for building and orchestrating AI agents.

Table of Contents

  • Core Design Philosophies
  • Key Features Comparison
  • Protocol Structure Examples
  • Advanced Features
  • Error Handling
  • Subscriptions and Notifications
  • Implementation Considerations

Core Design Philosophies

MCP A2A
Resource-centric architecture with URI-addressable resources Agent-centric design focused on standardized interoperability
Emphasizes flexible data access patterns (get, set, subscribe) Built around structured task management and agent workflows
Provides granular control with client-side workflow orchestration Formalizes agent discovery and capability advertisement
Designed for direct interaction with model capabilities Optimized for orchestrating multi-agent systems

Key Features Comparison

Common Ground

  • JSON-based Communication Structure
  • MIME Type Support for diverse content
  • Asynchronous Operation Support
  • AI Agent Interaction capabilities

Agent Discovery and Capabilities

A2A Approach – „AgentCard“ Structure: 

{
  "name": "DocumentAnalyzerAgent",
  "description": "Analyzes documents and extracts key information",
  "url": "https://doc-analyzer.example.com",
  "capabilities": {
    "streaming": true,
    "pushNotifications": true
  },
  "authentication": {
    "schemes": ["Bearer"]
  },
  "defaultInputModes": ["application/pdf", "text/plain"],
  "skills": [
    {
      "id": "extractEntities",
      "name": "Extract Entities",
      "description": "Identifies and extracts named entities from documents",
      "inputModes": ["application/pdf", "text/plain"],
      "outputModes": ["application/json"]
    }
  ]
}

MCP Approach – Resource-Based Discovery: 

{
  "method": "tools/list",
  "params": {}
}

// Response
{
  "result": {
    "tools": [
      {
        "name": "document_analyzer",
        "description": "Analyzes documents and extracts key information",
        "resources": [
          "/document_analyzer/extract_entities",
          "/document_analyzer/upload_document"
        ]
      }
    ]
  }
}

Protocol Structure Examples

MCP: Resource-Based Method Calls

  1. Resource Access Methods 
// GET resource
{
  "method": "resources/get",
  "params": {
    "uri": "/sentiment_analyzer/results",
    "params": {
      "textId": "doc-12345"
    }
  }
}

// SET resource
{
  "method": "resources/set",
  "params": {
    "uri": "/sentiment_analyzer/text",
    "content": {
      "type": "text/plain",
      "data": "I absolutely loved the product, though shipping was a bit slow."
    }
  }
}

// SUBSCRIBE to resource updates
{
  "method": "resources/subscribe",
  "params": {
    "uri": "/sentiment_analyzer/stream",
    "params": {
      "frequency": "realtime"
    }
  }
}

A2A: Agent-Based Task Management

  1. Task Submission 
{
  "type": "SendTaskRequest",
  "method": "tasks/send",
  "params": {
    "description": "Translate business proposal to Japanese",
    "steps": [
      {
        "agent_id": "TranslatorAgent",
        "skill_id": "translate",
        "input": [
          {
            "type": "data",
            "mimeType": "text/plain",
            "data": "We are pleased to submit our proposal for your consideration."
          }
        ],
        "parameters": {
          "sourceLanguage": "en",
          "targetLanguage": "ja",
          "formality": "formal"
        }
      }
    ]
  }
}
  1. Multi-Step Task Workflow 
{
  "type": "SendTaskRequest",
  "method": "tasks/send",
  "params": {
    "description": "Analyze customer feedback and prepare report",
    "steps": [
      {
        "step_id": "extract",
        "agent_id": "DataProcessorAgent",
        "skill_id": "extractFeedback",
        "input": [
          {
            "type": "data",
            "mimeType": "application/json",
            "data": {"source": "survey_responses.csv", "columns": ["date", "text", "rating"]}
          }
        ]
      },
      {
        "step_id": "analyze",
        "agent_id": "SentimentAnalyzerAgent",
        "skill_id": "batchAnalyze",
        "input": [
          {
            "type": "step_output",
            "step_id": "extract"
          }
        ],
        "parameters": {
          "aspects": ["pricing", "quality", "service"],
          "timeframe": "Q1_2024"
        }
      }
    ]
  }
}

Advanced Features

MCP: Resource Manipulation and State Management

Complex Resource Structure: 

{
  "method": "resources/set",
  "params": {
    "uri": "/chat_session/context",
    "content": {
      "type": "application/json",
      "data": {
        "sessionId": "sess-9876",
        "user": {
          "id": "user-12345",
          "preferences": {
            "language": "en-US",
            "expertise": "beginner",
            "verbosity": "detailed"
          }
        },
        "conversation": {
          "topic": "Technical Support",
          "priority": "high",
          "history": [
            {"role": "user", "content": "My application keeps crashing"},
            {"role": "assistant", "content": "Let's troubleshoot that. When does it crash?"}
          ]
        }
      }
    }
  }
}

A2A: Advanced Task Orchestration

Task Control Operations: 

{
  "type": "UpdateTaskRequest",
  "method": "tasks/update",
  "params": {
    "task_id": "task-123456",
    "operation": "pause",
    "reason": "Waiting for user input on parameter values"
  }
}

Error Handling

MCP Errors

{
  "error": {
    "code": -32601,
    "message": "Method not found",
    "data": {
      "requested_method": "resources/delete",
      "available_methods": ["resources/get", "resources/set", "resources/subscribe"]
    }
  }
}

A2A Errors

{
  "type": "ErrorResponse",
  "error": {
    "code": "AgentUnavailableError",
    "message": "The requested agent 'DataProcessorAgent' is currently unavailable",
    "details": {
      "estimated_availability": "2024-04-27T18:00:00Z",
      "alternatives": ["BackupDataProcessorAgent", "LegacyDataProcessorAgent"]
    }
  }
}

Subscriptions and Notifications

MCP Subscription Flow

// Subscribe
{
  "method": "resources/subscribe",
  "params": {
    "uri": "/market_data/stock_prices",
    "params": {
      "symbols": ["AAPL", "MSFT", "GOOGL"],
      "interval": "1m"
    }
  }
}

// Real-time update
{
  "method": "server/notification",
  "params": {
    "subscriptionId": "sub-abcdef123456",
    "content": {
      "timestamp": "2024-04-27T16:42:15Z",
      "updates": [
        {"symbol": "AAPL", "price": 198.42, "change": 0.57},
        {"symbol": "MSFT", "price": 412.65, "change": -0.32},
        {"symbol": "GOOGL", "price": 167.88, "change": 1.24}
      ]
    }
  }
}

A2A Event Notification

{
  "type": "EventNotification",
  "event": {
    "event_type": "TaskStatusChanged",
    "task_id": "task-567890",
    "previous_status": "Running",
    "current_status": "Completed",
    "timestamp": "2024-04-27T16:45:22Z",
    "details": {
      "completion_time": "12.4s",
      "resource_usage": {
        "compute_units": 0.0087,
        "storage_bytes": 25600
      }
    }
  }
}

Authentication and Security

MCP Authentication

{
  "method": "resources/set",
  "params": {
    "uri": "/system/auth",
    "content": {
      "type": "application/json",
      "data": {
        "api_key": "sk-12345abcdef",
        "session_id": "sess-678910"
      }
    }
  }
}

A2A Authentication

{
  "type": "AuthRequest",
  "method": "auth/authenticate",
  "params": {
    "agentId": "DataAnalysisAgent",
    "scheme": "Bearer",
    "credentials": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9..."
  }
}

Implementation Considerations

Choose MCP when:

  • You need fine-grained control over resource access
  • Your application requires client-side orchestration
  • You prefer a simpler, resource-based approach
  • Your system primarily involves direct client-model interaction

Choose A2A when:

  • You’re building a multi-agent ecosystem
  • You need standardized agent discovery and interoperability
  • Your workflows involve complex, multi-step tasks
  • You require formalized task state management

Note: Schemas are being enhanced and changed frequently. This guide will be updated periodically to reflect the latest changes.

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