Module airbyte_agent_sdk.connectors.customer_io

Customer-Io connector for Airbyte SDK.

Auto-generated from OpenAPI specification.

Sub-modules

• airbyte_agent_sdk.connectors.customer_io.connector
• airbyte_agent_sdk.connectors.customer_io.connector_model
• airbyte_agent_sdk.connectors.customer_io.models
• airbyte_agent_sdk.connectors.customer_io.types

Classes

AirbyteAuthConfig(**data: Any) : Authentication configuration for Airbyte hosted mode execution.

Pass this to the connector's auth_config parameter to use hosted mode, where API credentials are stored securely in Airbyte Cloud.

For hosted mode execution, provide client credentials with either:

• connector_id: Direct connector/source ID (skips lookup)
• workspace_name: Workspace name for connector lookup

Attributes: workspace_name: Workspace name for hosted mode connector lookup organization_id: Optional Airbyte organization ID for multi-org selection airbyte_client_id: Airbyte OAuth client ID (required for hosted mode) airbyte_client_secret: Airbyte OAuth client secret (required for hosted mode) connector_id: Specific connector/source ID (skips lookup if provided)

Examples:

Hosted mode with connector_id (no lookup needed)

connector = GongConnector( auth_config=AirbyteAuthConfig( airbyte_client_id="client_abc123", airbyte_client_secret="secret_xyz789", connector_id="existing-source-uuid" ) )

Hosted mode with workspace_name (lookup by workspace)

connector = GongConnector( auth_config=AirbyteAuthConfig( workspace_name="user-123", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc123", airbyte_client_secret="secret_xyz789" ) )

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel

Class variables

airbyte_client_id: str | None : The type of the None singleton.

airbyte_client_secret: str | None : The type of the None singleton.

connector_id: str | None : The type of the None singleton.

model_config : The type of the None singleton.

organization_id: str | None : The type of the None singleton.

workspace_name: str | None : The type of the None singleton.

AirbyteSearchMeta(**data: Any) : Pagination metadata for search responses.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel

Class variables

cursor: str | None : Cursor for fetching the next page of results.

has_more: bool : Whether more results are available.

model_config : The type of the None singleton.

took_ms: int | None : Time taken to execute the search in milliseconds.

AirbyteSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel
• typing.Generic

Descendants

• airbyte_agent_sdk.connectors.customer_io.models.AirbyteSearchResult[CampaignActionsSearchData]
• airbyte_agent_sdk.connectors.customer_io.models.AirbyteSearchResult[CampaignsSearchData]
• airbyte_agent_sdk.connectors.customer_io.models.AirbyteSearchResult[NewslettersSearchData]

Class variables

data: list[~D] : List of matching records.

meta: airbyte_agent_sdk.connectors.customer_io.models.AirbyteSearchMeta : Pagination metadata.

model_config : The type of the None singleton.

CampaignActionsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• airbyte_agent_sdk.connectors.customer_io.models.AirbyteSearchResult
• pydantic.main.BaseModel
• typing.Generic

CampaignsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• airbyte_agent_sdk.connectors.customer_io.models.AirbyteSearchResult
• pydantic.main.BaseModel
• typing.Generic

NewslettersSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• airbyte_agent_sdk.connectors.customer_io.models.AirbyteSearchResult
• pydantic.main.BaseModel
• typing.Generic

CampaignActionsSearchData(**data: Any) : Search result data for campaign_actions entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel

Class variables

bcc: str | None : BCC addresses

body: str | None : Action body content (HTML for emails)

campaign_id: int | None : Parent campaign ID

created: int | None : Creation timestamp (Unix)

deduplicate_id: str | None : Deduplication identifier

editor: str | None : Editor used to create the action

fake_bcc: bool | None : Whether to use fake BCC

from_: str | None : From address

from_id: str | None : Sender identity ID

headers: str | None : Custom email headers as JSON

id: str | None : Unique action identifier

language: str | None : Language variant

layout: str | None : Layout template used

model_config : The type of the None singleton.

name: str | None : Action name

parent_action_id: int | None : Parent action ID for language variants

preheader_text: str | None : Email preheader/preview text

preprocessor: str | None : CSS preprocessor setting

recipient: str | None : Recipient address

recipient_environment_id: int | None : Recipient environment ID

reply_to: str | None : Reply-to address

reply_to_id: str | None : Reply-to sender identity ID

request_method: str | None : HTTP request method for webhook actions

sending_state: str | None : Sending behavior (automatic or draft)

subject: str | None : Email subject line

type_: str | None : Action type (email, webhook, twilio, push, slack, in_app, whatsapp)

updated: int | None : Last update timestamp (Unix)

url: str | None : Webhook URL (for webhook actions)

CampaignsSearchData(**data: Any) : Search result data for campaigns entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel

Class variables

actions: list[typing.Any] | None : Actions defined in this campaign

active: bool | None : Whether the campaign is active

created: int | None : Creation timestamp (Unix)

created_by: str | None : Who created the campaign

date_attribute: str | None : Date attribute used for date-triggered campaigns

deduplicate_id: str | None : Deduplication identifier

event_name: str | None : Event name that triggers the campaign

first_started: int | None : When the campaign was first started (Unix)

frequency: str | None : How frequently a person can receive this campaign

id: int | None : Unique campaign identifier

model_config : The type of the None singleton.

msg_templates: list[typing.Any] | None : Message templates used in the campaign

name: str | None : Campaign name

start_hour: int | None : Hour of the day to trigger

start_minutes: int | None : Minute of the hour to trigger

state: str | None : Campaign status (draft, active, stopped)

tags: list[typing.Any] | None : Tags associated with the campaign

timezone: str | None : Timezone for trigger scheduling

trigger_segment_ids: list[typing.Any] | None : Segment IDs that trigger this campaign

type_: str | None : Campaign trigger type

updated: int | None : Last update timestamp (Unix)

use_customer_timezone: bool | None : Whether to use the customer's timezone

CustomerIoAuthConfig(**data: Any) : App API Key Authentication

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel

Class variables

app_api_key: str : Your Customer.io App API key. Generate one in your workspace settings at Settings > API Credentials > App API Key.

model_config : The type of the None singleton.

CustomerIoConnector(auth_config: CustomerIoAuthConfig | AirbyteAuthConfig | BaseModel | None = None, on_token_refresh: Any | None = None) : Type-safe Customer-Io API connector.

Auto-generated from OpenAPI specification with full type safety.

Initialize a new customer-io connector instance.

Supports both local and hosted execution modes:

• Local mode: Provide connector-specific auth config (e.g., CustomerIoAuthConfig)
• Hosted mode: Provide AirbyteAuthConfig with client credentials and either connector_id or workspace_name

Args: auth_config: Either connector-specific auth config for local mode, or AirbyteAuthConfig for hosted mode on_token_refresh: Optional callback for OAuth2 token refresh persistence. Called with new_tokens dict when tokens are refreshed. Can be sync or async. Example: lambda tokens: save_to_database(tokens) Examples:

Local mode (direct API calls)

connector = CustomerIoConnector(auth_config=CustomerIoAuthConfig(app_api_key="..."))

Hosted mode with explicit connector_id (no lookup needed)

connector = CustomerIoConnector( auth_config=AirbyteAuthConfig( airbyte_client_id="client_abc123", airbyte_client_secret="secret_xyz789", connector_id="existing-source-uuid" ) )

Hosted mode with lookup by workspace_name

connector = CustomerIoConnector( auth_config=AirbyteAuthConfig( workspace_name="user-123", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc123", airbyte_client_secret="secret_xyz789" ) )

Class variables

connector_name : The type of the None singleton.

connector_version : The type of the None singleton.

sdk_version : The type of the None singleton.

Static methods

tool_utils(func: _F | None = None, *, update_docstring: bool = True, max_output_chars: int | None = 100000, framework: FrameworkName | None = None, internal_retries: int = 0, should_internal_retry: Callable[[Exception, tuple[Any, ...], dict[str, Any]], bool] | None = None, exhausted_runtime_failure_message: Callable[[Exception, tuple[Any, ...], dict[str, Any]], str | None] | None = None) ‑> ~_F | Callable[[~_F], ~_F] : Decorator that adds tool utilities like docstring augmentation and output limits.

Composes :func:airbyte_agent_sdk.translation.translate_exceptions for runtime wrapping (sync/async branch + output-size check + framework signal translation + optional internal retry loop), and adds connector-specific docstring augmentation on top of it.

Usage: @mcp.tool() @CustomerIoConnector.tool_utils async def execute(entity: str, action: str, params: dict): ...

@mcp.tool() @CustomerIoConnector.tool_utils(update_docstring=False, max_output_chars=None) async def execute(entity: str, action: str, params: dict): ...

@mcp.tool() @CustomerIoConnector.tool_utils(framework="pydantic_ai", internal_retries=2) async def execute(entity: str, action: str, params: dict): ...

Args: update_docstring: When True, append connector capabilities to doc. max_output_chars: Max serialized output size before raising. Use None to disable. framework: One of "pydantic_ai" | "langchain" | "openai_agents" | "mcp". Defaults to None → auto-detect by attempting each framework's canonical import in order. Explicit always wins. internal_retries: How many transient runtime failures (429/5xx, network, timeout) to retry silently before surfacing. Default 0. Forwarded to :func:airbyte_agent_sdk.translation.translate_exceptions. should_internal_retry: Optional predicate (error, args, kwargs) -> bool further restricting which retryable errors are safe for this specific tool. Forwarded to :func:airbyte_agent_sdk.translation.translate_exceptions. exhausted_runtime_failure_message: Optional callback (error, args, kwargs) -> str | None. Invoked after internal retries are exhausted OR were skipped via should_internal_retry returning False. Forwarded to :func:airbyte_agent_sdk.translation.translate_exceptions.

Instance variables

connector_id: str | None : Get the connector/source ID (only available in hosted mode).

Returns: The connector ID if in hosted mode, None if in local mode.

Methods

check(self) ‑> airbyte_agent_sdk.connectors.customer_io.models.CustomerIoCheckResult : Perform a health check to verify connectivity and credentials.

Executes a lightweight list operation (limit=1) to validate that the connector can communicate with the API and credentials are valid.

Returns: CustomerIoCheckResult with status ("healthy" or "unhealthy") and optional error message

Example: result = await connector.check() if result.status == "healthy": print("Connection verified!") else: print(f"Check failed: {result.error}")

close(self) : Close the connector and release resources.

entity_schema(self, entity: str) ‑> dict[str, typing.Any] | None : Get the JSON schema for an entity.

Args: entity: Entity name (e.g., "contacts", "companies")

Returns: JSON schema dict describing the entity structure, or None if not found.

Example: schema = connector.entity_schema("contacts") if schema: print(f"Contact properties: {list(schema.get('properties', {}).keys())}")

execute(self, entity: str, action: "Literal['list', 'get', 'create', 'update', 'context_store_search']", params: Mapping[str, Any] | None = None) ‑> Any : Execute an entity operation with full type safety.

This is the recommended interface for blessed connectors as it:

• Uses the same signature as non-blessed connectors
• Provides full IDE autocomplete for entity/action/params
• Makes migration from generic to blessed connectors seamless

Args: entity: Entity name (e.g., "customers") action: Operation action (e.g., "create", "get", "list") params: Operation parameters (typed based on entity+action)

Returns: Typed response based on the operation

Example: customer = await connector.execute( entity="customers", action="get", params={"id": "cus_123"} )

list_entities(self) ‑> list[dict[str, typing.Any]] : Get structured data about available entities, actions, and parameters.

Returns a list of entity descriptions with:

• entity_name: Name of the entity (e.g., "contacts", "deals")
• description: Entity description from the first endpoint
• available_actions: List of actions (e.g., ["list", "get", "create"])
• parameters: Dict mapping action -> list of parameter dicts

Example: entities = connector.list_entities() for entity in entities: print(f"{entity['entity_name']}: {entity['available_actions']}")

CustomerIoReplicationConfig(**data: Any) : Replication Configuration - Settings for data replication from Customer.io.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel

Class variables

model_config : The type of the None singleton.

start_date: str : UTC date and time in the format YYYY-MM-DDTHH:mm:ssZ from which to start replicating data.

NewslettersSearchData(**data: Any) : Search result data for newsletters entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel

Class variables

content_ids: list[typing.Any] | None : Content variant IDs for this newsletter

created: int | None : Creation timestamp (Unix)

deduplicate_id: str | None : Deduplication identifier

id: int | None : Unique newsletter identifier

model_config : The type of the None singleton.

name: str | None : Newsletter name

sent_at: int | None : When the newsletter was last sent (Unix)

tags: list[typing.Any] | None : Tags associated with the newsletter

type_: str | None : Channel type (email, webhook, twilio, push, in_app, inbox)

updated: int | None : Last update timestamp (Unix)