Snapchat-Marketing

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

The Snapchat-Marketing agent connector is a Python package that equips AI agents to interact with Snapchat-Marketing through strongly typed, well-documented tools. It's ready to use directly in your Python app, in an agent framework, or exposed through an MCP.

Connector for the Snapchat Marketing API (Ads API). Provides access to Snapchat advertising entities including organizations, ad accounts, campaigns, ad squads, ads, creatives, media, and audience segments. Supports OAuth2 authentication with automatic token refresh.

Example prompts

The Snapchat-Marketing connector is optimized to handle prompts like these.

• List all organizations I belong to
• Show me all ad accounts for my organization
• List all campaigns in my ad account
• Show me the ad squads for my ad account
• List all ads in my ad account
• Show me the creatives for my ad account
• List all media files in my ad account
• Show me the audience segments in my ad account
• Which campaigns are currently active?
• What ad squads have the highest daily budget?
• Show me ads that are pending review
• Find campaigns created in the last month

Unsupported prompts

The Snapchat-Marketing connector isn't currently able to handle prompts like these.

• Create a new campaign
• Update an ad's status
• Delete a creative
• Show me ad performance statistics

Entities and actions

This connector supports the following entities and actions. For more details, see this connector's full reference documentation.

Entity	Actions
Organizations	List, Get, Context Store Search
Adaccounts	List, Get, Context Store Search
Campaigns	List, Get, Context Store Search
Adsquads	List, Get, Context Store Search
Ads	List, Get, Context Store Search
Creatives	List, Get, Context Store Search
Media	List, Get, Context Store Search
Segments	List, Get, Context Store Search

Snapchat-Marketing API docs

See the official Snapchat-Marketing API reference.

SDK installation

uv pip install airbyte-agent-sdk

SDK usage

Connectors can run in hosted or open source mode.

Hosted

In hosted mode, API credentials are stored securely in Airbyte Agents. You provide your Airbyte credentials instead. If your Airbyte client can access multiple organizations, also set organization_id.

This example assumes you've already authenticated your connector with Airbyte. See Authentication to learn more about authenticating. If you need a step-by-step guide, see the hosted execution tutorial.

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

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

Open source

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

Pydantic AI

Pydantic AI

from pydantic_ai import Agent
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>"
    )
)

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.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>"
    )
)

@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.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>"
    )
)

# 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.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>"
    )
)

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

Authentication

For all authentication options, see the connector's authentication documentation.

Version information

Connector version: 1.0.5