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A2A Protocol

A2A Sample Methods and JSON Responses

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A2A Sample Methods and JSON Responses

This section provides illustrative JSON examples of common A2A interactions. Timestamps, context IDs, and request/response IDs are for demonstration purposes. For brevity, some optional fields might be omitted if not central to the example.

1. Fetching Authenticated Extended Agent Card

Scenario: A client discovers a public Agent Card indicating support for an authenticated extended card and wants to retrieve the full details.

  1. Client fetches the public Agent Card:

    GET https://example.com/.well-known/agent.json

    Server responds with the public Agent Card (like the example in Section 5.6), including supportsAuthenticatedExtendedCard: true (at the root level) and securitySchemes.

  2. Client identifies required authentication from the public card.

  3. Client obtains necessary credentials out-of-band (e.g., performs OAuth 2.0 flow with Google, resulting in an access token).

  4. Client fetches the authenticated extended Agent Card:

    GET https://example.com/a2a/agent/authenticatedExtendedCard
Authorization: Bearer <obtained_access_token>

  5. Server authenticates and authorizes the request.

  6. Server responds with the full Agent Card:

2. Basic Execution (Synchronous / Polling Style)

2.1. Task-based Response

Scenario: Client asks a simple question, and the agent responds quickly with a task

  1. Client sends a message using message/send:

    {
  "jsonrpc": "2.0",
  "id": 1,
  "method": "message/send",
  "params": {
    "message": {
      "role": "user",
      "parts": [
        {
          "kind": "text",
          "text": "tell me a joke"
        }
      ],
      "messageId": "9229e770-767c-417b-a0b0-f0741243c589"
    },
    "metadata": {}
  }
}

  2. Server processes the request, creates a task and responds (task completes quickly)

    {
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "id": "363422be-b0f9-4692-a24d-278670e7c7f1",
    "contextId": "c295ea44-7543-4f78-b524-7a38915ad6e4",
    "status": {
      "state": "completed"
    },
    "artifacts": [
      {
        "artifactId": "9b6934dd-37e3-4eb1-8766-962efaab63a1",
        "name": "joke",
        "parts": [
          {
            "kind": "text",
            "text": "Why did the chicken cross the road? To get to the other side!"
          }
        ]
      }
    ],
    "history": [
      {
        "role": "user",
        "parts": [
          {
            "kind": "text",
            "text": "tell me a joke"
          }
        ],
        "messageId": "9229e770-767c-417b-a0b0-f0741243c589",
        "taskId": "363422be-b0f9-4692-a24d-278670e7c7f1",
        "contextId": "c295ea44-7543-4f78-b524-7a38915ad6e4"
      }
    ],
    "kind": "task",
    "metadata": {}
  }
}

2.2. Direct Message Response

Scenario: Client asks a simple question, and the agent responds quickly without a task

  1. Client sends a message using message/send:

    {
  "jsonrpc": "2.0",
  "id": 1,
  "method": "message/send",
  "params": {
    "message": {
      "role": "user",
      "parts": [
        {
          "kind": "text",
          "text": "tell me a joke"
        }
      ],
      "messageId": "9229e770-767c-417b-a0b0-f0741243c589"
    },
    "metadata": {}
  }
}

  2. Server processes the request, responds quickly without a task

    {
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "messageId": "363422be-b0f9-4692-a24d-278670e7c7f1",
    "contextId": "c295ea44-7543-4f78-b524-7a38915ad6e4",
    "parts": [
      {
        "kind": "text",
        "text": "Why did the chicken cross the road? To get to the other side!"
      }
    ],
    "kind": "message",
    "metadata": {}
  }
}

If the task were longer-running, the server might initially respond with status.state: "working". The client would then periodically call tasks/get with params: {"id": "363422be-b0f9-4692-a24d-278670e7c7f1"} until the task reaches a terminal state.

3. Streaming Task Execution (SSE)

Scenario: Client asks the agent to write a long paper describing an attached picture.

  1. Client sends a message and subscribes using message/stream:

    {
  "method": "message/stream",
  "params": {
    "message": {
      "role": "user",
      "parts": [
        {
          "kind": "text",
          "text": "write a long paper describing the attached pictures"
        },
        {
          "kind": "file",
          "file": {
            "mimeType": "image/png",
            "data": "<base64-encoded-content>"
          }
        }
      ],
      "messageId": "bbb7dee1-cf5c-4683-8a6f-4114529da5eb"
    },
    "metadata": {}
  }
}

  2. Server responds with HTTP 200 OK, Content-Type: text/event-stream, and starts sending SSE events:

    Event 1: Task status update - working

    data: {
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "id": "225d6247-06ba-4cda-a08b-33ae35c8dcfa",
    "contextId": "05217e44-7e9f-473e-ab4f-2c2dde50a2b1",
    "status": {
      "state": "submitted",
      "timestamp":"2025-04-02T16:59:25.331844"
    },
    "history": [
      {
        "role": "user",
        "parts": [
          {
            "kind": "text",
            "text": "write a long paper describing the attached pictures"
          },
          {
            "kind": "file",
            "file": {
              "mimeType": "image/png",
              "data": "<base64-encoded-content>"
            }
          }
        ],
        "messageId": "bbb7dee1-cf5c-4683-8a6f-4114529da5eb",
        "taskId": "225d6247-06ba-4cda-a08b-33ae35c8dcfa",
        "contextId": "05217e44-7e9f-473e-ab4f-2c2dde50a2b1"
      }
    ],
    "kind": "task",
    "metadata": {}
  }
}

data: {
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "taskId": "225d6247-06ba-4cda-a08b-33ae35c8dcfa",
    "contextId": "05217e44-7e9f-473e-ab4f-2c2dde50a2b1",
    "artifact": {
      "artifactId": "9b6934dd-37e3-4eb1-8766-962efaab63a1",
      "parts": [
        {"type":"text", "text": "<section 1...>"}
      ]
    },
    "append": false,
    "lastChunk": false,
    "kind":"artifact-update"
  }
}

data: {
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "taskId": "225d6247-06ba-4cda-a08b-33ae35c8dcfa",
    "contextId": "05217e44-7e9f-473e-ab4f-2c2dde50a2b1",
    "artifact": {
      "artifactId": "9b6934dd-37e3-4eb1-8766-962efaab63a1",
      "parts": [
        {"type":"text", "text": "<section 2...>"}
      ],
    },
    "append": true,
    "lastChunk": false,
    "kind":"artifact-update"
  }
}


data: {
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "taskId": "225d6247-06ba-4cda-a08b-33ae35c8dcfa",
    "contextId": "05217e44-7e9f-473e-ab4f-2c2dde50a2b1",
    "artifact": {
      "artifactId": "9b6934dd-37e3-4eb1-8766-962efaab63a1",
      "parts": [
        {"type":"text", "text": "<section 3...>"}
      ]
    },
    "append": true,
    "lastChunk": true,
    "kind":"artifact-update"
  }
}

data: {
  "jsonrpc": "2.0",
  "id": 1,
  "result": {
    "taskId": "225d6247-06ba-4cda-a08b-33ae35c8dcfa",
    "contextId": "05217e44-7e9f-473e-ab4f-2c2dde50a2b1",
    "status": {
      "state": "completed",
      "timestamp":"2025-04-02T16:59:35.331844"
    },
    "final": true,
    "kind":"status-update"
  }
}

    (Server closes the SSE connection after the final:true event).

4. Multi-Turn Interaction (Input Required)

Scenario: Client wants to book a flight, and the agent needs more information.

  1. Client sends a message using message/send:

    {
  "jsonrpc": "2.0",
  "id": "req-003",
  "method": "message/send",
  "params": {
    "message": {
      "role": "user",
      "parts": [{ "kind": "text", "text": "I'd like to book a flight." }]
    },
    "messageId": "c53ba666-3f97-433c-a87b-6084276babe2"
  }
}

  2. Server responds, task state is input-required:

    {
  "jsonrpc": "2.0",
  "id": "req-003",
  "result": {
    "id": "3f36680c-7f37-4a5f-945e-d78981fafd36",
    "contextId": "c295ea44-7543-4f78-b524-7a38915ad6e4",
    "status": {
      "state": "input-required",
      "message": {
        "role": "agent",
        "parts": [
          {
            "kind": "text",
            "text": "Sure, I can help with that! Where would you like to fly to, and from where? Also, what are your preferred travel dates?"
          }
        ],
        "messageId": "c2e1b2dd-f200-4b04-bc22-1b0c65a1aad2",
        "taskId": "3f36680c-7f37-4a5f-945e-d78981fafd36",
        "contextId": "c295ea44-7543-4f78-b524-7a38915ad6e4"
      },
      "timestamp": "2024-03-15T10:10:00Z"
    },
    "history": [
      {
        "role": "user",
        "parts": [
          {
            "kind": "text",
            "text": "I'd like to book a flight."
          }
        ],
        "messageId": "c53ba666-3f97-433c-a87b-6084276babe2",
        "taskId": "3f36680c-7f37-4a5f-945e-d78981fafd36",
        "contextId": "c295ea44-7543-4f78-b524-7a38915ad6e4"
      }
    ],
    "kind": "task"
  }
}

  3. Client message/send (providing the requested input, using the same task ID):

    {
  "jsonrpc": "2.0",
  "id": "req-004",
  "method": "message/send",
  "params": {
    "message": {
      "role": "user",
      "parts": [
        {
          "kind": "text",
          "text": "I want to fly from New York (JFK) to London (LHR) around October 10th, returning October 17th."
        }
      ],
      "contextId": "c295ea44-7543-4f78-b524-7a38915ad6e4",
      "taskId": "3f36680c-7f37-4a5f-945e-d78981fafd36",
      "messageId": "0db1d6c4-3976-40ed-b9b8-0043ea7a03d3"
    },
    "configuration": {
      "blocking": true
    }
  }
}

  4. Server processes the new input and responds (e.g., task completed or more input needed):

    {
  "jsonrpc": "2.0",
  "id": "req-004",
  "result": {
    "id": "3f36680c-7f37-4a5f-945e-d78981fafd36",
    "contextId": "c295ea44-7543-4f78-b524-7a38915ad6e4",
    "status": {
      "state": "completed",
      "message": {
        "role": "agent",
        "parts": [
          {
            "kind": "text",
            "text": "Okay, I've found a flight for you. Confirmation XYZ123. Details are in the artifact."
          }
        ]
      }
    },
    "artifacts": [
      {
        "artifactId": "9b6934dd-37e3-4eb1-8766-962efaab63a1",
        "name": "FlightItinerary.json",
        "parts": [
          {
            "kind": "data",
            "data": {
              "confirmationId": "XYZ123",
              "from": "JFK",
              "to": "LHR",
              "departure": "2024-10-10T18:00:00Z",
              "arrival": "2024-10-11T06:00:00Z",
              "returnDeparture": "..."
            }
          }
        ]
      }
    ],
    "history": [
      {
        "role": "user",
        "parts": [
          {
            "kind": "text",
            "text": "I'd like to book a flight."
          }
        ],
        "messageId": "c53ba666-3f97-433c-a87b-6084276babe2",
        "taskId": "3f36680c-7f37-4a5f-945e-d78981fafd36",
        "contextId": "c295ea44-7543-4f78-b524-7a38915ad6e4"
      },
      {
        "role": "agent",
        "parts": [
          {
            "kind": "text",
            "text": "Sure, I can help with that! Where would you like to fly to, and from where? Also, what are your preferred travel dates?"
          }
        ],
        "messageId": "c2e1b2dd-f200-4b04-bc22-1b0c65a1aad2",
        "taskId": "3f36680c-7f37-4a5f-945e-d78981fafd36",
        "contextId": "c295ea44-7543-4f78-b524-7a38915ad6e4"
      },
      {
        "role": "user",
        "parts": [
          {
            "kind": "text",
            "text": "I want to fly from New York (JFK) to London (LHR) around October 10th, returning October 17th."
          }
        ],
        "contextId": "c295ea44-7543-4f78-b524-7a38915ad6e4",
        "taskId": "3f36680c-7f37-4a5f-945e-d78981fafd36",
        "messageId": "0db1d6c4-3976-40ed-b9b8-0043ea7a03d3"
      }
    ],
    "kind": "task",
    "metadata": {}
  }
}

5. Push Notification Setup and Usage

5.1. Webhook Configuration and Notification Flow

Scenario: Client requests a long-running report generation and wants to be notified via webhook when it's done.

  1. Client message/send with pushNotification config:

    {
  "jsonrpc": "2.0",
  "id": "req-005",
  "method": "message/send",
  "params": {
    "message": {
      "role": "user",
      "parts": [
        {
          "kind": "text",
          "text": "Generate the Q1 sales report. This usually takes a while. Notify me when it's ready."
        }
      ],
      "messageId": "6dbc13b5-bd57-4c2b-b503-24e381b6c8d6"
    },
    "configuration": {
      "pushNotificationConfig": {
        "url": "https://client.example.com/webhook/a2a-notifications",
        "token": "secure-client-token-for-task-aaa",
        "authentication": {
          "schemes": ["Bearer"]
          // Assuming server knows how to get a Bearer token for this webhook audience,
          // or this implies the webhook is public/uses the 'token' for auth.
          // 'credentials' could provide more specifics if needed by the server.
        }
      }
    }
  }
}

  2. Server acknowledges the task (e.g., status submitted or working):

    {
  "jsonrpc": "2.0",
  "id": "req-005",
  "result": {
    "id": "43667960-d455-4453-b0cf-1bae4955270d",
    "contextId": "c295ea44-7543-4f78-b524-7a38915ad6e4",
    "status": { "state": "submitted", "timestamp": "2024-03-15T11:00:00Z" }
    // ... other fields ...
  }
}

  3. (Later) A2A Server completes the task and POSTs a notification to https://client.example.com/webhook/a2a-notifications:

    • HTTP Headers might include:
      • Authorization: Bearer <server_jwt_for_webhook_audience> (if server authenticates to webhook)
      • Content-Type: application/json
      • X-A2A-Notification-Token: secure-client-token-for-task-aaa
    • HTTP Body (Task object is sent as JSON payload):
    {
  "id": "43667960-d455-4453-b0cf-1bae4955270d",
  "contextId": "c295ea44-7543-4f78-b524-7a38915ad6e4",
  "status": { "state": "completed", "timestamp": "2024-03-15T18:30:00Z" },
  "kind": "task"
  // ... other fields ...
}

  4. Client's Webhook Service:

    • Receives the POST.
    • Validates the Authorization header (if applicable).
    • Validates the X-A2A-Notification-Token.
    • Internally processes the notification (e.g., updates application state, notifies end user).

6. File Exchange (Upload and Download)

6.1. Image Processing Workflow

Scenario: Client sends an image for analysis, and the agent returns a modified image.

  1. Client message/send with a FilePart (uploading image bytes):

    {
  "jsonrpc": "2.0",
  "id": "req-007",
  "method": "message/send",
  "params": {
    "message": {
      "role": "user",
      "parts": [
        {
          "kind": "text",
          "text": "Analyze this image and highlight any faces."
        },
        {
          "kind": "file",
          "file": {
            "name": "input_image.png",
            "mimeType": "image/png",
            "bytes": "iVBORw0KGgoAAAANSUhEUgAAAAUA..." // Base64 encoded image data
          }
        }
      ],
      "messageId": "6dbc13b5-bd57-4c2b-b503-24e381b6c8d6"
    }
  }
}

  2. Server processes the image and responds with a FilePart in an artifact (e.g., providing a URI to the modified image):

    {
  "jsonrpc": "2.0",
  "id": "req-007",
  "result": {
    "id": "43667960-d455-4453-b0cf-1bae4955270d",
    "contextId": "c295ea44-7543-4f78-b524-7a38915ad6e4",
    "status": { "state": "completed", "timestamp": "2024-03-15T12:05:00Z" },
    "artifacts": [
      {
        "artifactId": "9b6934dd-37e3-4eb1-8766-962efaab63a1",
        "name": "processed_image_with_faces.png",
        "parts": [
          {
            "kind": "file",
            "file": {
              "name": "output.png",
              "mimeType": "image/png",
              // Server might provide a URI to a temporary storage location
              "uri": "https://storage.example.com/processed/task-bbb/output.png?token=xyz"
              // Or, alternatively, it could return bytes directly:
              // "bytes": "ASEDGhw0KGgoAAAANSUhEUgAA..."
            }
          }
        ]
      }
    ],
    "kind": "task"
  }
}

7. Structured Data Exchange (Requesting and Providing JSON)

7.1. Schema-based Data Request

Scenario: Client asks for a list of open support tickets in a specific JSON format.

  1. Client message/send, Part.metadata hints at desired output schema/Media Type: (Note: A2A doesn't formally standardize schema negotiation in v0.2.0, but metadata can be used for such hints by convention between client/server).

    {
  "jsonrpc": "2.0",
  "id": 9,
  "method": "message/send",
  "params": {
    "message": {
      "role": "user",
      "parts": [
        {
          "kind": "text",
          "text": "Show me a list of my open IT tickets",
          "metadata": {
            "mimeType": "application/json",
            "schema": {
              "type": "array",
              "items": {
                "type": "object",
                "properties": {
                  "ticketNumber": { "type": "string" },
                  "description": { "type": "string" }
                }
              }
            }
          }
        }
      ],
      "messageId": "85b26db5-ffbb-4278-a5da-a7b09dea1b47"
    },
    "metadata": {}
  }
}

  2. Server responds with structured JSON data:

    {
  "jsonrpc": "2.0",
  "id": 9,
  "result": {
    "id": "d8c6243f-5f7a-4f6f-821d-957ce51e856c",
    "contextId": "c295ea44-7543-4f78-b524-7a38915ad6e4",
    "status": {
      "state": "completed",
      "timestamp": "2025-04-17T17:47:09.680794"
    },
    "artifacts": [
      {
        "artifactId": "c5e0382f-b57f-4da7-87d8-b85171fad17c",
        "parts": [
          {
            "kind": "text",
            "text": "[{\"ticketNumber\":\"REQ12312\",\"description\":\"request for VPN access\"},{\"ticketNumber\":\"REQ23422\",\"description\":\"Add to DL - team-gcp-onboarding\"}]"
          }
        ]
      }
    ],
    "kind": "task"
  }
}

8. Summary

These examples illustrate the flexibility of A2A in handling various interaction patterns and data types. The workflows covered include:

  • Authentication: Fetching authenticated extended agent cards
  • Execution Patterns: Synchronous, asynchronous, and streaming task execution
  • Interaction Models: Single-turn and multi-turn conversations
  • Notification Systems: Push notifications via webhooks
  • Data Exchange: File uploads/downloads and structured JSON data

Implementers should refer to the detailed object definitions for all fields and constraints when implementing these workflows.

Go A2A

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