Module airbyte_agent_sdk.connectors.intercom.connector

Intercom connector.

Classes

AdminsQuery(connector: IntercomConnector) : Query class for Admins entity operations.

Initialize query with connector reference.

Methods

get(self, id: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.Admin : Get a single admin by ID

Args: id: Admin ID **kwargs: Additional parameters

Returns: Admin

list(self, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.IntercomExecuteResult[list[Admin]] : Returns a list of all admins in the workspace

Returns: AdminsListResult

CompaniesQuery(connector: IntercomConnector) : Query class for Companies entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: CompaniesSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.intercom.models.AirbyteSearchResult[CompaniesSearchData] : Search companies records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (CompaniesSearchFilter):

app_id: The ID of the application associated with the company
company_id: The unique identifier of the company
created_at: The date and time when the company was created
custom_attributes: Custom attributes specific to the company
id: The ID of the company
industry: The industry in which the company operates
monthly_spend: The monthly spend of the company
name: The name of the company
plan: Details of the company's subscription plan
remote_created_at: The remote date and time when the company was created
segments: Segments associated with the company
session_count: The number of sessions related to the company
size: The size of the company
tags: Tags associated with the company
type_: The type of the company
updated_at: The date and time when the company was last updated
user_count: The number of users associated with the company
website: The website of the company

Args: query: Filter and sort conditions. Supports operators like eq, neq, gt, gte, lt, lte, in, like, fuzzy, keyword, not, and, or. Example: {"filter": {"eq": {"status": "active"}}} limit: Maximum results to return (default 1000) cursor: Pagination cursor from previous response's meta.cursor fields: Field paths to include in results. Each path is a list of keys for nested access. Example: [["id"], ["user", "name"]] returns id and user.name fields.

Returns: CompaniesSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

create(self, company_id: str, name: str | None = None, plan: str | None = None, monthly_spend: float | None = None, size: int | None = None, website: str | None = None, industry: str | None = None, custom_attributes: dict[str, Any] | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.Company : Create a new company or update an existing one by company_id

Args: company_id: A unique identifier for the company from your system name: The name of the company plan: The name of the plan the company is on monthly_spend: The monthly spend of the company size: The number of employees in the company website: The URL of the company website industry: The industry the company operates in custom_attributes: Custom attributes for the company **kwargs: Additional parameters

Returns: Company

get(self, id: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.Company : Get a single company by ID

Args: id: Company ID **kwargs: Additional parameters

Returns: Company

list(self, per_page: int | None = None, starting_after: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.IntercomExecuteResultWithMeta[list[Company], CompaniesListResultMeta] : Returns a paginated list of companies

Args: per_page: Number of companies to return per page starting_after: Cursor for pagination **kwargs: Additional parameters

Returns: CompaniesListResult

Args: name: The name of the company plan: The name of the plan the company is on monthly_spend: The monthly spend of the company size: The number of employees in the company website: The URL of the company website industry: The industry the company operates in custom_attributes: Custom attributes for the company id: Company ID **kwargs: Additional parameters

Returns: Company

ContactsQuery(connector: IntercomConnector) : Query class for Contacts entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: ContactsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.intercom.models.AirbyteSearchResult[ContactsSearchData] : Search contacts records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (ContactsSearchFilter):

android_app_name: The name of the Android app associated with the contact.
android_app_version: The version of the Android app associated with the contact.
android_device: The device used by the contact for Android.
android_last_seen_at: The date and time when the contact was last seen on Android.
android_os_version: The operating system version of the Android device.
android_sdk_version: The SDK version of the Android device.
avatar: URL pointing to the contact's avatar image.
browser: The browser used by the contact.
browser_language: The language preference set in the contact's browser.
browser_version: The version of the browser used by the contact.
companies: Companies associated with the contact.
created_at: The date and time when the contact was created.
custom_attributes: Custom attributes defined for the contact.
email: The email address of the contact.
external_id: External identifier for the contact.
has_hard_bounced: Flag indicating if the contact has hard bounced.
id: The unique identifier of the contact.
ios_app_name: The name of the iOS app associated with the contact.
ios_app_version: The version of the iOS app associated with the contact.
ios_device: The device used by the contact for iOS.
ios_last_seen_at: The date and time when the contact was last seen on iOS.
ios_os_version: The operating system version of the iOS device.
ios_sdk_version: The SDK version of the iOS device.
language_override: Language override set for the contact.
last_contacted_at: The date and time when the contact was last contacted.
last_email_clicked_at: The date and time when the contact last clicked an email.
last_email_opened_at: The date and time when the contact last opened an email.
last_replied_at: The date and time when the contact last replied.
last_seen_at: The date and time when the contact was last seen overall.
location: Location details of the contact.
marked_email_as_spam: Flag indicating if the contact's email was marked as spam.
name: The name of the contact.
notes: Notes associated with the contact.
opted_in_subscription_types: Subscription types the contact opted into.
opted_out_subscription_types: Subscription types the contact opted out from.
os: Operating system of the contact's device.
owner_id: The unique identifier of the contact's owner.
phone: The phone number of the contact.
referrer: Referrer information related to the contact.
role: Role or position of the contact.
signed_up_at: The date and time when the contact signed up.
sms_consent: Consent status for SMS communication.
social_profiles: Social profiles associated with the contact.
tags: Tags associated with the contact.
type_: Type of contact.
unsubscribed_from_emails: Flag indicating if the contact unsubscribed from emails.
unsubscribed_from_sms: Flag indicating if the contact unsubscribed from SMS.
updated_at: The date and time when the contact was last updated.
utm_campaign: Campaign data from UTM parameters.
utm_content: Content data from UTM parameters.
utm_medium: Medium data from UTM parameters.
utm_source: Source data from UTM parameters.
utm_term: Term data from UTM parameters.
workspace_id: The unique identifier of the workspace associated with the contact.

Returns: ContactsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

Args: role: The role of the contact (user or lead) external_id: A unique identifier for the contact from your system email: The contact's email address phone: The contact's phone number name: The contact's full name avatar: An image URL for the contact's avatar signed_up_at: Sign up timestamp (Unix) last_seen_at: Last seen timestamp (Unix) owner_id: The ID of the admin assigned as owner unsubscribed_from_emails: Whether the contact is unsubscribed from emails custom_attributes: Custom attributes for the contact **kwargs: Additional parameters

Returns: Contact

get(self, id: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.Contact : Get a single contact by ID

Args: id: Contact ID **kwargs: Additional parameters

Returns: Contact

list(self, per_page: int | None = None, starting_after: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.IntercomExecuteResultWithMeta[list[Contact], ContactsListResultMeta] : Returns a paginated list of contacts in the workspace

Args: per_page: Number of contacts to return per page starting_after: Cursor for pagination - get contacts after this ID **kwargs: Additional parameters

Returns: ContactsListResult

Returns: Contact

ConversationsQuery(connector: IntercomConnector) : Query class for Conversations entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: ConversationsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.intercom.models.AirbyteSearchResult[ConversationsSearchData] : Search conversations records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (ConversationsSearchFilter):

admin_assignee_id: The ID of the administrator assigned to the conversation
ai_agent: Data related to AI Agent involvement in the conversation
ai_agent_participated: Indicates whether AI Agent participated in the conversation
assignee: The assigned user responsible for the conversation.
contacts: List of contacts involved in the conversation.
conversation_message: The main message content of the conversation.
conversation_rating: Ratings given to the conversation by the customer and teammate.
created_at: The timestamp when the conversation was created
custom_attributes: Custom attributes associated with the conversation
customer_first_reply: Timestamp indicating when the customer first replied.
customers: List of customers involved in the conversation
first_contact_reply: Timestamp indicating when the first contact replied.
id: The unique ID of the conversation
linked_objects: Linked objects associated with the conversation
open: Indicates if the conversation is open or closed
priority: The priority level of the conversation
read: Indicates if the conversation has been read
redacted: Indicates if the conversation is redacted
sent_at: The timestamp when the conversation was sent
sla_applied: Service Level Agreement details applied to the conversation.
snoozed_until: Timestamp until the conversation is snoozed
source: Source details of the conversation.
state: The state of the conversation (e.g., new, in progress)
statistics: Statistics related to the conversation.
tags: Tags applied to the conversation.
team_assignee_id: The ID of the team assigned to the conversation
teammates: List of teammates involved in the conversation.
title: The title of the conversation
topics: Topics associated with the conversation.
type_: The type of the conversation
updated_at: The timestamp when the conversation was last updated
user: The user related to the conversation.
waiting_since: Timestamp since waiting for a response

Returns: ConversationsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

get(self, id: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.Conversation : Get a single conversation by ID

Args: id: Conversation ID **kwargs: Additional parameters

Returns: Conversation

list(self, per_page: int | None = None, starting_after: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.IntercomExecuteResultWithMeta[list[Conversation], ConversationsListResultMeta] : Returns a paginated list of conversations

Args: per_page: Number of conversations to return per page starting_after: Cursor for pagination **kwargs: Additional parameters

Returns: ConversationsListResult

IntercomConnector(auth_config: IntercomAuthConfig | AirbyteAuthConfig | BaseModel | None = None, on_token_refresh: Any | None = None) : Type-safe Intercom API connector.

Auto-generated from OpenAPI specification with full type safety.

Initialize a new intercom connector instance.

Supports both local and hosted execution modes:

Local mode: Provide connector-specific auth config (e.g., IntercomAuthConfig)
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 = IntercomConnector(auth_config=IntercomAuthConfig(access_token="..."))

Hosted mode with explicit connector_id (no lookup needed)

connector = IntercomConnector( 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 = IntercomConnector( 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: "'IntercomAuthConfig'", name: str | None = None, replication_config: "'IntercomReplicationConfig' | None" = None, source_template_id: str | None = None) : Create a new hosted connector on Airbyte Cloud.

This factory method:

Creates a source on Airbyte Cloud with the provided credentials
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: Typed replication settings. 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 IntercomConnector instance configured in hosted mode

Example:

Create a new hosted connector with API key auth

connector = await IntercomConnector.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=IntercomAuthConfig(access_token="..."), )

With replication config (required for this connector):

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

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

@mcp.tool() @IntercomConnector.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 IntercomConnector.create(...) print(f"Created connector: {connector.connector_id}")

Methods

check(self) ‑> airbyte_agent_sdk.connectors.intercom.models.IntercomCheckResult : 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: IntercomCheckResult 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', 'create', 'get', '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']}")

InternalArticlesQuery(connector: IntercomConnector) : Query class for InternalArticles entity operations.

Initialize query with connector reference.

Methods

create(self, title: str, owner_id: int, author_id: int, body: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.InternalArticle : Create a new internal article in the workspace

Args: title: The title of the article body: The content of the article in HTML owner_id: The ID of the owner of the article author_id: The ID of the author of the article **kwargs: Additional parameters

Returns: InternalArticle

NotesQuery(connector: IntercomConnector) : Query class for Notes entity operations.

Initialize query with connector reference.

Methods

create(self, body: str, contact_id: str, admin_id: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.Note : Create a note on an existing contact

Args: body: The body of the note in HTML format admin_id: The ID of the admin creating the note contact_id: Contact ID to add note to **kwargs: Additional parameters

Returns: Note

SegmentsQuery(connector: IntercomConnector) : Query class for Segments entity operations.

Initialize query with connector reference.

Methods

get(self, id: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.Segment : Get a single segment by ID

Args: id: Segment ID **kwargs: Additional parameters

Returns: Segment

list(self, include_count: bool | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.IntercomExecuteResult[list[Segment]] : Returns a list of all segments in the workspace

Args: include_count: Include count of contacts in each segment **kwargs: Additional parameters

Returns: SegmentsListResult

TagsQuery(connector: IntercomConnector) : Query class for Tags entity operations.

Initialize query with connector reference.

Methods

create(self, name: str, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.Tag : Create a new tag or update an existing one

Args: name: The name of the tag **kwargs: Additional parameters

Returns: Tag

get(self, id: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.Tag : Get a single tag by ID

Args: id: Tag ID **kwargs: Additional parameters

Returns: Tag

list(self, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.IntercomExecuteResult[list[Tag]] : Returns a list of all tags in the workspace

Returns: TagsListResult

TeamsQuery(connector: IntercomConnector) : Query class for Teams entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: TeamsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.intercom.models.AirbyteSearchResult[TeamsSearchData] : Search teams records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (TeamsSearchFilter):

admin_ids: Array of user IDs representing the admins of the team.
id: Unique identifier for the team.
name: Name of the team.
type_: Type of team (e.g., 'internal', 'external').

Returns: TeamsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

get(self, id: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.Team : Get a single team by ID

Args: id: Team ID **kwargs: Additional parameters

Returns: Team

list(self, **kwargs) ‑> airbyte_agent_sdk.connectors.intercom.models.IntercomExecuteResult[list[Team]] : Returns a list of all teams in the workspace

Returns: TeamsListResult

Classes​

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Local mode (direct API calls)

Hosted mode with explicit connector_id (no lookup needed)

Hosted mode with lookup by workspace_name

Class variables​

Static methods​

Create a new hosted connector with API key auth

With replication config (required for this connector):

Use the connector

Instance variables​

Methods​

Methods​

Methods​

Methods​

Methods​

Methods​

Classes

Methods

Methods

Methods

Methods

Class variables

Static methods

Instance variables

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