Snapchat-Marketing authentication

This connector is optimized for AI agents. For the data replication connector, see Snapchat Marketing.

This page documents the authentication and configuration options for the Snapchat-Marketing agent connector.

Authentication

Open source execution

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

OAuth

This authentication method isn't available for this connector.

Token

credentials fields you need:

Field Name	Type	Required	Description
client_id	str	Yes	The Client ID of your Snapchat developer application
client_secret	str	Yes	The Client Secret of your Snapchat developer application
refresh_token	str	Yes	Refresh Token to renew the expired Access Token

Example request:

from airbyte_agent_sdk.connectors.snapchat_marketing import SnapchatMarketingConnector
from airbyte_agent_sdk.connectors.snapchat_marketing.models import SnapchatMarketingAuthConfig

connector = SnapchatMarketingConnector(
    auth_config=SnapchatMarketingAuthConfig(
        client_id="<The Client ID of your Snapchat developer application>",
        client_secret="<The Client Secret of your Snapchat developer application>",
        refresh_token="<Refresh Token to renew the expired Access Token>"
    )
)

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

This authentication method isn't available for this connector.

Bring your own OAuth flow

This authentication method isn't available for this connector.

Token

Create a connector with Token credentials.

credentials fields you need:

Field Name	Type	Required	Description
client_id	str	Yes	The Client ID of your Snapchat developer application
client_secret	str	Yes	The Client Secret of your Snapchat developer application
refresh_token	str	Yes	Refresh Token to renew the expired Access Token

replication_config fields you need:

Field Name	Type	Required	Description
start_date	str (date)	Yes	Date in YYYY-MM-DD format. Data before this date will not be replicated.

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": "Snapchat-Marketing",
    "name": "My Snapchat-Marketing Connector",
    "credentials": {
      "client_id": "<The Client ID of your Snapchat developer application>",
      "client_secret": "<The Client Secret of your Snapchat developer application>",
      "refresh_token": "<Refresh Token to renew the expired Access Token>"
    },
    "replication_config": {
      "start_date": "<Date in YYYY-MM-DD format. Data before this date will not be replicated.>"
    }
  }'

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 SnapchatMarketingConnector and reads AIRBYTE_CLIENT_ID / AIRBYTE_CLIENT_SECRET from the environment:

Pydantic AI

Pydantic AI

from pydantic_ai import Agent
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.snapchat_marketing import SnapchatMarketingConnector

connector = connect("snapchat-marketing", workspace_name="<your_workspace_name>")

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

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

LangChain

LangChain

from langchain_core.tools import tool
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.snapchat_marketing import SnapchatMarketingConnector

connector = connect("snapchat-marketing", workspace_name="<your_workspace_name>")

@tool
@SnapchatMarketingConnector.tool_utils
async def snapchat_marketing_execute(entity: str, action: str, params: dict | None = None):
    """Execute Snapchat-Marketing 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

OpenAI Agents

from agents import Agent, function_tool
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.snapchat_marketing import SnapchatMarketingConnector

connector = connect("snapchat-marketing", 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)
@SnapchatMarketingConnector.tool_utils(framework="openai_agents")
async def snapchat_marketing_execute(entity: str, action: str, params: dict | None = None):
    """Execute Snapchat-Marketing 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="Snapchat-Marketing Assistant", tools=[snapchat_marketing_execute])

FastMCP

FastMCP

from fastmcp import FastMCP
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.snapchat_marketing import SnapchatMarketingConnector

connector = connect("snapchat-marketing", workspace_name="<your_workspace_name>")

mcp = FastMCP("Snapchat-Marketing Agent")

@mcp.tool
@SnapchatMarketingConnector.tool_utils
async def snapchat_marketing_execute(entity: str, action: str, params: dict | None = None):
    """Execute Snapchat-Marketing 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

Pydantic AI

from pydantic_ai import Agent
from airbyte_agent_sdk.connectors.snapchat_marketing import SnapchatMarketingConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

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

LangChain

LangChain

from langchain_core.tools import tool
from airbyte_agent_sdk.connectors.snapchat_marketing import SnapchatMarketingConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = SnapchatMarketingConnector(
    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
@SnapchatMarketingConnector.tool_utils
async def snapchat_marketing_execute(entity: str, action: str, params: dict | None = None):
    """Execute Snapchat-Marketing 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

OpenAI Agents

from agents import Agent, function_tool
from airbyte_agent_sdk.connectors.snapchat_marketing import SnapchatMarketingConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = SnapchatMarketingConnector(
    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)
@SnapchatMarketingConnector.tool_utils(framework="openai_agents")
async def snapchat_marketing_execute(entity: str, action: str, params: dict | None = None):
    """Execute Snapchat-Marketing 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="Snapchat-Marketing Assistant", tools=[snapchat_marketing_execute])

FastMCP

FastMCP

from fastmcp import FastMCP
from airbyte_agent_sdk.connectors.snapchat_marketing import SnapchatMarketingConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = SnapchatMarketingConnector(
    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("Snapchat-Marketing Agent")

@mcp.tool
@SnapchatMarketingConnector.tool_utils
async def snapchat_marketing_execute(entity: str, action: str, params: dict | None = None):
    """Execute Snapchat-Marketing 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": {}}'