Klaviyo

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

The Klaviyo agent connector is a Python package that equips AI agents to interact with Klaviyo 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.

Klaviyo is a marketing automation platform that helps businesses build customer relationships through personalized email, SMS, and push notifications. This connector provides access to Klaviyo's core entities including profiles, lists, campaigns, events, metrics, flows, and email templates for marketing analytics and customer engagement insights.

Example prompts

The Klaviyo connector is optimized to handle prompts like these.

List all profiles in my Klaviyo account
Show me details for a recent profile
Show me all email lists
Show me details for a recent email list
What campaigns have been created?
Show me details for a recent campaign
Show me all email campaigns
List all events for tracking customer actions
Show me all metrics (event types)
Show me details for a recent metric
What automated flows are configured?
Show me details for a recent flow
List all email templates
Show me details for a recent email template

Unsupported prompts

The Klaviyo connector isn't currently able to handle prompts like these.

Create a new profile
Update a profile's email address
Delete a list
Send an email campaign
Add a profile to a list

Entities and actions

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

Entity	Actions
Profiles	List, Get, Context Store Search
Lists	List, Get, Context Store Search
Campaigns	List, Get, Context Store Search
Events	List, Context Store Search
Metrics	List, Get, Context Store Search
Flows	List, Get, Context Store Search
Email Templates	List, Get, Context Store Search

Klaviyo API docs

See the official Klaviyo 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 KlaviyoConnector 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.klaviyo import KlaviyoConnector

connector = connect("klaviyo", workspace_name="<your_workspace_name>")

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

@agent.tool_plain
@KlaviyoConnector.tool_utils
async def klaviyo_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.klaviyo import KlaviyoConnector

connector = connect("klaviyo", workspace_name="<your_workspace_name>")

@tool
@KlaviyoConnector.tool_utils
async def klaviyo_execute(entity: str, action: str, params: dict | None = None):
    """Execute Klaviyo 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.klaviyo import KlaviyoConnector

connector = connect("klaviyo", 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)
@KlaviyoConnector.tool_utils(framework="openai_agents")
async def klaviyo_execute(entity: str, action: str, params: dict | None = None):
    """Execute Klaviyo 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="Klaviyo Assistant", tools=[klaviyo_execute])

FastMCP
from fastmcp import FastMCP
from airbyte_agent_sdk import connect
from airbyte_agent_sdk.connectors.klaviyo import KlaviyoConnector

connector = connect("klaviyo", workspace_name="<your_workspace_name>")

mcp = FastMCP("Klaviyo Agent")

@mcp.tool
@KlaviyoConnector.tool_utils
async def klaviyo_execute(entity: str, action: str, params: dict | None = None):
    """Execute Klaviyo 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
LangChain
OpenAI Agents
FastMCP

Pydantic AI
from pydantic_ai import Agent
from airbyte_agent_sdk.connectors.klaviyo import KlaviyoConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = KlaviyoConnector(
    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
@KlaviyoConnector.tool_utils
async def klaviyo_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.klaviyo import KlaviyoConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = KlaviyoConnector(
    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
@KlaviyoConnector.tool_utils
async def klaviyo_execute(entity: str, action: str, params: dict | None = None):
    """Execute Klaviyo 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.klaviyo import KlaviyoConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = KlaviyoConnector(
    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)
@KlaviyoConnector.tool_utils(framework="openai_agents")
async def klaviyo_execute(entity: str, action: str, params: dict | None = None):
    """Execute Klaviyo 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="Klaviyo Assistant", tools=[klaviyo_execute])

FastMCP
from fastmcp import FastMCP
from airbyte_agent_sdk.connectors.klaviyo import KlaviyoConnector
from airbyte_agent_sdk.types import AirbyteAuthConfig

connector = KlaviyoConnector(
    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("Klaviyo Agent")

@mcp.tool
@KlaviyoConnector.tool_utils
async def klaviyo_execute(entity: str, action: str, params: dict | None = None):
    """Execute Klaviyo 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
LangChain
OpenAI Agents
FastMCP

Pydantic AI
from pydantic_ai import Agent
from airbyte_agent_sdk.connectors.klaviyo import KlaviyoConnector
from airbyte_agent_sdk.connectors.klaviyo.models import KlaviyoAuthConfig

connector = KlaviyoConnector(
    auth_config=KlaviyoAuthConfig(
        api_key="<Your Klaviyo private API key>"
    )
)

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

@agent.tool_plain
@KlaviyoConnector.tool_utils
async def klaviyo_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.klaviyo import KlaviyoConnector
from airbyte_agent_sdk.connectors.klaviyo.models import KlaviyoAuthConfig

connector = KlaviyoConnector(
    auth_config=KlaviyoAuthConfig(
        api_key="<Your Klaviyo private API key>"
    )
)

@tool
@KlaviyoConnector.tool_utils
async def klaviyo_execute(entity: str, action: str, params: dict | None = None):
    """Execute Klaviyo 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.klaviyo import KlaviyoConnector
from airbyte_agent_sdk.connectors.klaviyo.models import KlaviyoAuthConfig

connector = KlaviyoConnector(
    auth_config=KlaviyoAuthConfig(
        api_key="<Your Klaviyo private API key>"
    )
)

# strict_mode=False because `params: dict` is permissive and the default strict
# JSON schema rejects objects with additionalProperties.
@function_tool(strict_mode=False)
@KlaviyoConnector.tool_utils(framework="openai_agents")
async def klaviyo_execute(entity: str, action: str, params: dict | None = None):
    """Execute Klaviyo 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="Klaviyo Assistant", tools=[klaviyo_execute])

FastMCP
from fastmcp import FastMCP
from airbyte_agent_sdk.connectors.klaviyo import KlaviyoConnector
from airbyte_agent_sdk.connectors.klaviyo.models import KlaviyoAuthConfig

connector = KlaviyoConnector(
    auth_config=KlaviyoAuthConfig(
        api_key="<Your Klaviyo private API key>"
    )
)

mcp = FastMCP("Klaviyo Agent")

@mcp.tool
@KlaviyoConnector.tool_utils
async def klaviyo_execute(entity: str, action: str, params: dict | None = None):
    """Execute Klaviyo 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: 1.0.6

Example prompts​

Unsupported prompts​

Entities and actions​

Klaviyo API docs​

SDK installation​

SDK usage​

Hosted​

Open source​

Authentication​

Version information​