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Module airbyte_agent_sdk.connectors.mailchimp

Mailchimp connector for Airbyte SDK.

Auto-generated from OpenAPI specification.

Sub-modules

  • airbyte_agent_sdk.connectors.mailchimp.connector
  • airbyte_agent_sdk.connectors.mailchimp.connector_model
  • airbyte_agent_sdk.connectors.mailchimp.models
  • airbyte_agent_sdk.connectors.mailchimp.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.mailchimp.models.AirbyteSearchResult[CampaignsSearchData]
  • airbyte_agent_sdk.connectors.mailchimp.models.AirbyteSearchResult[EmailActivitySearchData]
  • airbyte_agent_sdk.connectors.mailchimp.models.AirbyteSearchResult[ListsSearchData]
  • airbyte_agent_sdk.connectors.mailchimp.models.AirbyteSearchResult[ReportsSearchData]

Class variables

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

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

model_config : The type of the None singleton.

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.mailchimp.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

EmailActivitySearchResult(**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.mailchimp.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

ListsSearchResult(**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.mailchimp.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

ReportsSearchResult(**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.mailchimp.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

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

ab_split_opts: dict[str, typing.Any] | None : A/B Testing options for a campaign.

archive_url: str | None : The link to the campaign's archive version in ISO 8601 format.

content_type: str | None : How the campaign's content is put together.

create_time: str | None : The date and time the campaign was created in ISO 8601 format.

delivery_status: dict[str, typing.Any] | None : Updates on campaigns in the process of sending.

emails_sent: int | None : The total number of emails sent for this campaign.

id: str | None : A string that uniquely identifies this campaign.

long_archive_url: str | None : The original link to the campaign's archive version.

model_config : The type of the None singleton.

needs_block_refresh: bool | None : Determines if the campaign needs its blocks refreshed by opening the web-based campaign editor. D...

parent_campaign_id: str | None : If this campaign is the child of another campaign, this identifies the parent campaign. For Examp...

recipients: dict[str, typing.Any] | None : List settings for the campaign.

report_summary: dict[str, typing.Any] | None : For sent campaigns, a summary of opens, clicks, and e-commerce data.

resendable: bool | None : Determines if the campaign qualifies to be resent to non-openers.

rss_opts: dict[str, typing.Any] | None : RSS options for a campaign.

send_time: str | None : The date and time a campaign was sent.

settings: dict[str, typing.Any] | None : The settings for your campaign, including subject, from name, reply-to address, and more.

social_card: dict[str, typing.Any] | None : The preview for the campaign, rendered by social networks like Facebook and Twitter. [Learn more]...

status: str | None : The current status of the campaign.

tracking: dict[str, typing.Any] | None : The tracking options for a campaign.

type_: str | None : There are four types of campaigns y...

variate_settings: dict[str, typing.Any] | None : The settings specific to A/B test campaigns.

web_id: int | None : The ID used in the Mailchimp web application. View this campaign in your Mailchimp account at `ht...

EmailActivitySearchData(**data: Any) : Search result data for email_activity 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

action: str | None : One of the following actions: 'open', 'click', or 'bounce'

campaign_id: str | None : The unique id for the campaign.

email_address: str | None : Email address for a subscriber.

email_id: str | None : The MD5 hash of the lowercase version of the list member's email address.

ip: str | None : The IP address recorded for the action.

list_id: str | None : The unique id for the list.

list_is_active: bool | None : The status of the list used, namely if it's deleted or disabled.

model_config : The type of the None singleton.

timestamp: str | None : The date and time recorded for the action in ISO 8601 format.

type_: str | None : If the action is a 'bounce', the type of bounce received: 'hard', 'soft'.

url: str | None : If the action is a 'click', the URL on which the member clicked.

ListsSearchData(**data: Any) : Search result data for lists 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

beamer_address: str | None : The list's Email Beamer address.

campaign_defaults: dict[str, typing.Any] | None : Default values for campaigns created for this list.

contact: dict[str, typing.Any] | None : Contact information displayed in campaign footers to comply with international spam laws.

date_created: str | None : The date and time that this list was created in ISO 8601 format.

double_optin: bool | None : Whether or not to require the subscriber to confirm subscription via email.

email_type_option: bool | None : Whether the list supports multiple formats for emails. When set to true, subscribers can choose...

has_welcome: bool | None : Whether or not this list has a welcome automation connected.

id: str | None : A string that uniquely identifies this list.

list_rating: int | None : An auto-generated activity score for the list (0-5).

marketing_permissions: bool | None : Whether or not the list has marketing permissions (eg. GDPR) enabled.

model_config : The type of the None singleton.

modules: list[typing.Any] | None : Any list-specific modules installed for this list.

name: str | None : The name of the list.

notify_on_subscribe: str | None : The email address to send subscribe notifications to.

notify_on_unsubscribe: str | None : The email address to send unsubscribe notifications to.

permission_reminder: str | None : The permission reminder for the list.

stats: dict[str, typing.Any] | None : Stats for the list. Many of these are cached for at least five minutes.

subscribe_url_long: str | None : The full version of this list's subscribe form (host will vary).

subscribe_url_short: str | None : Our EepURL shortened version of this list's subscribe form.

use_archive_bar: bool | None : Whether campaigns for this list use the Archive Bar in archives by default.

visibility: str | None : Whether this list is public or private.

web_id: int | None : The ID used in the Mailchimp web application. View this list in your Mailchimp account at `https:...

MailchimpAuthConfig(**data: Any) : 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

api_key: str : Your Mailchimp API key. You can find this in your Mailchimp account under Account > Extras > API keys.

model_config : The type of the None singleton.

MailchimpConnector(auth_config: MailchimpAuthConfig | AirbyteAuthConfig | BaseModel | None = None, on_token_refresh: Any | None = None, data_center: str | None = None) : Type-safe Mailchimp API connector.

Auto-generated from OpenAPI specification with full type safety.

Initialize a new mailchimp connector instance.

Supports both local and hosted execution modes:

  • Local mode: Provide connector-specific auth config (e.g., MailchimpAuthConfig)
  • 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) data_center: The data center for your Mailchimp account (e.g., us1, us2, us6) Examples:

Local mode (direct API calls)

connector = MailchimpConnector(auth_config=MailchimpAuthConfig(api_key="..."))

Hosted mode with explicit connector_id (no lookup needed)

connector = MailchimpConnector( 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 = MailchimpConnector( 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

create(*, airbyte_config: AirbyteAuthConfig, auth_config: "'MailchimpAuthConfig'", name: str | None = None, replication_config: dict[str, Any] | None = None, source_template_id: str | None = None) ‑> airbyte_agent_sdk.connectors.mailchimp.connector.MailchimpConnector : Create a new hosted connector on Airbyte Cloud.

This factory method:

  1. Creates a source on Airbyte Cloud with the provided credentials
  2. Returns a connector configured with the new connector_id

Args: airbyte_config: Airbyte hosted auth config with client credentials and workspace_name. Optionally include organization_id for multi-org request routing. auth_config: Typed auth config (same as local mode) name: Optional source name (defaults to connector name + workspace_name) replication_config: Optional replication settings dict. Required for connectors with x-airbyte-replication-config (REPLICATION mode sources). source_template_id: Source template ID. Required when organization has multiple source templates for this connector type.

Returns: A MailchimpConnector instance configured in hosted mode

Example:

Create a new hosted connector with API key auth

connector = await MailchimpConnector.create( airbyte_config=AirbyteAuthConfig( workspace_name="my-workspace", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc", airbyte_client_secret="secret_xyz", ), auth_config=MailchimpAuthConfig(api_key="..."), )

Use the connector

result = await connector.execute("entity", "list", {})

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() @MailchimpConnector.tool_utils async def execute(entity: str, action: str, params: dict): ...

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

@mcp.tool() @MailchimpConnector.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.

Example: connector = await MailchimpConnector.create(...) print(f"Created connector: {connector.connector_id}")

Methods

check(self) ‑> airbyte_agent_sdk.connectors.mailchimp.models.MailchimpCheckResult : 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: MailchimpCheckResult 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', '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']}")

ReportsSearchData(**data: Any) : Search result data for reports 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

ab_split: dict[str, typing.Any] | None : General stats about different groups of an A/B Split campaign. Does not return information about ...

abuse_reports: int | None : The number of abuse reports generated for this campaign.

bounces: dict[str, typing.Any] | None : An object describing the bounce summary for the campaign.

campaign_title: str | None : The title of the campaign.

clicks: dict[str, typing.Any] | None : An object describing the click activity for the campaign.

delivery_status: dict[str, typing.Any] | None : Updates on campaigns in the process of sending.

ecommerce: dict[str, typing.Any] | None : E-Commerce stats for a campaign.

emails_sent: int | None : The total number of emails sent for this campaign.

facebook_likes: dict[str, typing.Any] | None : An object describing campaign engagement on Facebook.

forwards: dict[str, typing.Any] | None : An object describing the forwards and forward activity for the campaign.

id: str | None : A string that uniquely identifies this campaign.

industry_stats: dict[str, typing.Any] | None : The average campaign statistics for your industry.

list_id: str | None : The unique list id.

list_is_active: bool | None : The status of the list used, namely if it's deleted or disabled.

list_name: str | None : The name of the list.

list_stats: dict[str, typing.Any] | None : The average campaign statistics for your list. This won't be present if we haven't calculated i...

model_config : The type of the None singleton.

opens: dict[str, typing.Any] | None : An object describing the open activity for the campaign.

preview_text: str | None : The preview text for the campaign.

rss_last_send: str | None : For RSS campaigns, the date and time of the last send in ISO 8601 format.

send_time: str | None : The date and time a campaign was sent in ISO 8601 format.

share_report: dict[str, typing.Any] | None : The url and password for the VIP report.

subject_line: str | None : The subject line for the campaign.

timeseries: list[typing.Any] | None : An hourly breakdown of the performance of the campaign over the first 24 hours.

timewarp: list[typing.Any] | None : An hourly breakdown of sends, opens, and clicks if a campaign is sent using timewarp.

type_: str | None : The type of campaign (regular, plain-text, ab_split, rss, automation, variate, or auto).

unsubscribed: int | None : The total number of unsubscribed members for this campaign.