Amazon-Ads authentication

This connector is optimized for AI agents. For the data replication connector, see Amazon Ads.

This page documents the authentication and configuration options for the Amazon-Ads agent connector.

Authentication

Open source execution

In open source mode, you provide API credentials directly to the connector.

OAuth

credentials fields you need:

Field Name	Type	Required	Description
`client_id`	`str`	No	The client ID of your Amazon Ads API application
`client_secret`	`str`	No	The client secret of your Amazon Ads API application
`refresh_token`	`str`	Yes	The refresh token obtained from the OAuth authorization flow

Example request:

from airbyte_agent_sdk.connectors.amazon_ads import AmazonAdsConnector
from airbyte_agent_sdk.connectors.amazon_ads.models import AmazonAdsAuthConfig

connector = AmazonAdsConnector(
    auth_config=AmazonAdsAuthConfig(
        client_id="<The client ID of your Amazon Ads API application>",
        client_secret="<The client secret of your Amazon Ads API application>",
        refresh_token="<The refresh token obtained from the OAuth authorization flow>"
    )
)

Token

This authentication method isn't available for this connector.

Hosted execution

In hosted mode, you first create a connector via the Airbyte Agent API (providing your OAuth or Token credentials), then execute operations using either the Python SDK or API. If you need a step-by-step guide, see the developer quickstart.

OAuth

Create a connector with OAuth credentials.

credentials fields you need:

Field Name	Type	Required	Description
`client_id`	`str`	No	The client ID of your Amazon Ads API application
`client_secret`	`str`	No	The client secret of your Amazon Ads API application
`refresh_token`	`str`	Yes	The refresh token obtained from the OAuth authorization flow

Example request:

curl -X POST "https://api.airbyte.ai/api/v1/integrations/connectors" \
  -H "Authorization: Bearer <YOUR_BEARER_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{
    "workspace_name": "<WORKSPACE_NAME>",
    "connector_type": "Amazon-Ads",
    "name": "My Amazon-Ads Connector",
    "credentials": {
      "client_id": "<The client ID of your Amazon Ads API application>",
      "client_secret": "<The client secret of your Amazon Ads API application>",
      "refresh_token": "<The refresh token obtained from the OAuth authorization flow>"
    }
  }'

Bring your own OAuth flow

To implement your own OAuth flow, use Airbyte's server-side OAuth API endpoints. For a complete guide, see Build your own OAuth flow.

Step 1: Initiate the OAuth flow

Request a consent URL for your user.

Field Name	Type	Required	Description
`workspace_name`	`string`	Yes	Your unique identifier for the workspace
`connector_type`	`string`	Yes	The connector type (e.g., "Amazon-Ads")
`redirect_url`	`string`	Yes	URL to redirect to after OAuth authorization

Example request:

curl -X POST "https://api.airbyte.ai/api/v1/integrations/connectors/oauth/initiate" \
  -H "Authorization: Bearer <YOUR_BEARER_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{
    "workspace_name": "<WORKSPACE_NAME>",
    "connector_type": "Amazon-Ads",
    "redirect_url": "https://yourapp.com/oauth/callback"
  }'

Redirect your user to the consent_url from the response.

Step 2: Handle the callback

After the user authorizes access, Airbyte automatically creates the connector and redirects them to your redirect_url with a connector_id query parameter. You don't need to make a separate API call to create the connector.

https://yourapp.com/oauth/callback?connector_id=<connector_id>

Extract the connector_id from the callback URL and store it for future operations. For error handling and a complete implementation example, see Build your own OAuth flow.

Token

This authentication method isn't available for this connector.

Execution

After creating the connector, execute operations using either the Python SDK or API. If your Airbyte client can access multiple organizations, include organization_id in AirbyteAuthConfig and X-Organization-Id in raw API calls.

Python SDK

The connect() factory returns a fully typed AmazonAdsConnector and reads AIRBYTE_CLIENT_ID / AIRBYTE_CLIENT_SECRET from the environment:

Pydantic AI
LangChain
OpenAI Agents
FastMCP

Pydantic AI
from pydantic_ai import Agent
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.amazon_ads import AmazonAdsConnector

connector = connect("amazon-ads", workspace_name="<your_workspace_name>")

agent = Agent("openai:gpt-4o")

@agent.tool_plain
@AmazonAdsConnector.tool_utils
async def amazon_ads_execute(entity: str, action: str, params: dict | None = None):
    return await connector.execute(entity, action, params or {})

LangChain
from langchain_core.tools import tool
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.amazon_ads import AmazonAdsConnector

connector = connect("amazon-ads", workspace_name="<your_workspace_name>")

@tool
@AmazonAdsConnector.tool_utils
async def amazon_ads_execute(entity: str, action: str, params: dict | None = None):
    """Execute Amazon-Ads connector operations."""
    result = await connector.execute(entity, action, params or {})
    # connector.execute returns a Pydantic envelope for typed actions; fall back to raw data otherwise.
    return result.model_dump(mode="json") if hasattr(result, "model_dump") else result

OpenAI Agents
from agents import Agent, function_tool
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.amazon_ads import AmazonAdsConnector

connector = connect("amazon-ads", workspace_name="<your_workspace_name>")

# strict_mode=False because `params: dict` is permissive and the default strict
# JSON schema rejects objects with additionalProperties.
@function_tool(strict_mode=False)
@AmazonAdsConnector.tool_utils(framework="openai_agents")
async def amazon_ads_execute(entity: str, action: str, params: dict | None = None):
    """Execute Amazon-Ads connector operations."""
    result = await connector.execute(entity, action, params or {})
    return result.model_dump(mode="json") if hasattr(result, "model_dump") else result

agent = Agent(name="Amazon-Ads Assistant", tools=[amazon_ads_execute])

FastMCP
from fastmcp import FastMCP
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.amazon_ads import AmazonAdsConnector

connector = connect("amazon-ads", workspace_name="<your_workspace_name>")

mcp = FastMCP("Amazon-Ads Agent")

@mcp.tool
@AmazonAdsConnector.tool_utils
async def amazon_ads_execute(entity: str, action: str, params: dict | None = None):
    """Execute Amazon-Ads connector operations."""
    result = await connector.execute(entity, action, params or {})
    return result.model_dump(mode="json") if hasattr(result, "model_dump") else result

Or pass credentials explicitly (equivalent, useful when you're not loading them from the environment): Pydantic AI

Pydantic AI
LangChain
OpenAI Agents
FastMCP

Pydantic AI
from pydantic_ai import Agent
from airbyte_agent_sdk.connectors.amazon_ads import AmazonAdsConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = AmazonAdsConnector(
    auth_config=AirbyteAuthConfig(
        workspace_name="<your_workspace_name>",
        organization_id="<your_organization_id>",  # Optional for multi-org clients
        airbyte_client_id="<your-client-id>",
        airbyte_client_secret="<your-client-secret>"
    )
)

agent = Agent("openai:gpt-4o")

@agent.tool_plain
@AmazonAdsConnector.tool_utils
async def amazon_ads_execute(entity: str, action: str, params: dict | None = None):
    return await connector.execute(entity, action, params or {})

LangChain
from langchain_core.tools import tool
from airbyte_agent_sdk.connectors.amazon_ads import AmazonAdsConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = AmazonAdsConnector(
    auth_config=AirbyteAuthConfig(
        workspace_name="<your_workspace_name>",
        organization_id="<your_organization_id>",  # Optional for multi-org clients
        airbyte_client_id="<your-client-id>",
        airbyte_client_secret="<your-client-secret>"
    )
)

@tool
@AmazonAdsConnector.tool_utils
async def amazon_ads_execute(entity: str, action: str, params: dict | None = None):
    """Execute Amazon-Ads connector operations."""
    result = await connector.execute(entity, action, params or {})
    # connector.execute returns a Pydantic envelope for typed actions; fall back to raw data otherwise.
    return result.model_dump(mode="json") if hasattr(result, "model_dump") else result

OpenAI Agents
from agents import Agent, function_tool
from airbyte_agent_sdk.connectors.amazon_ads import AmazonAdsConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = AmazonAdsConnector(
    auth_config=AirbyteAuthConfig(
        workspace_name="<your_workspace_name>",
        organization_id="<your_organization_id>",  # Optional for multi-org clients
        airbyte_client_id="<your-client-id>",
        airbyte_client_secret="<your-client-secret>"
    )
)

# strict_mode=False because `params: dict` is permissive and the default strict
# JSON schema rejects objects with additionalProperties.
@function_tool(strict_mode=False)
@AmazonAdsConnector.tool_utils(framework="openai_agents")
async def amazon_ads_execute(entity: str, action: str, params: dict | None = None):
    """Execute Amazon-Ads connector operations."""
    result = await connector.execute(entity, action, params or {})
    return result.model_dump(mode="json") if hasattr(result, "model_dump") else result

agent = Agent(name="Amazon-Ads Assistant", tools=[amazon_ads_execute])

FastMCP
from fastmcp import FastMCP
from airbyte_agent_sdk.connectors.amazon_ads import AmazonAdsConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = AmazonAdsConnector(
    auth_config=AirbyteAuthConfig(
        workspace_name="<your_workspace_name>",
        organization_id="<your_organization_id>",  # Optional for multi-org clients
        airbyte_client_id="<your-client-id>",
        airbyte_client_secret="<your-client-secret>"
    )
)

mcp = FastMCP("Amazon-Ads Agent")

@mcp.tool
@AmazonAdsConnector.tool_utils
async def amazon_ads_execute(entity: str, action: str, params: dict | None = None):
    """Execute Amazon-Ads connector operations."""
    result = await connector.execute(entity, action, params or {})
    return result.model_dump(mode="json") if hasattr(result, "model_dump") else result

API

curl -X POST 'https://api.airbyte.ai/api/v1/integrations/connectors/<connector_id>/execute' \
  -H 'Authorization: Bearer <YOUR_BEARER_TOKEN>' \
  -H 'X-Organization-Id: <YOUR_ORGANIZATION_ID>' \
  -H 'Content-Type: application/json' \
  -d '{"entity": "<entity>", "action": "<action>", "params": {}}'

Configuration

The Amazon-Ads connector requires the following configuration variables. These variables are used to construct the base API URL. Pass them via the config parameter when initializing the connector.

Variable	Type	Required	Default	Description
`region`	`string`	Yes	https://advertising-api.amazon.com	The Amazon Ads API endpoint URL based on region:

NA (North America): https://advertising-api.amazon.com
EU (Europe): https://advertising-api-eu.amazon.com
FE (Far East): https://advertising-api-fe.amazon.com |

Authentication​

Open source execution​

OAuth​

Token​

Hosted execution​

OAuth​

Bring your own OAuth flow​

Step 1: Initiate the OAuth flow​

Step 2: Handle the callback​

Token​

Execution​

Configuration​

Authentication

Open source execution

OAuth

Token

Hosted execution

OAuth

Bring your own OAuth flow

Step 1: Initiate the OAuth flow

Step 2: Handle the callback

Token

Execution

Configuration