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Module airbyte_agent_sdk.connectors.slack

Slack connector for Airbyte SDK.

Auto-generated from OpenAPI specification.

Sub-modules​

  • airbyte_agent_sdk.connectors.slack.connector
  • airbyte_agent_sdk.connectors.slack.connector_model
  • airbyte_agent_sdk.connectors.slack.models
  • airbyte_agent_sdk.connectors.slack.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.slack.models.AirbyteSearchResult[ChannelMessagesSearchData]
  • airbyte_agent_sdk.connectors.slack.models.AirbyteSearchResult[ChannelsSearchData]
  • airbyte_agent_sdk.connectors.slack.models.AirbyteSearchResult[ThreadsSearchData]
  • airbyte_agent_sdk.connectors.slack.models.AirbyteSearchResult[UsersSearchData]

Class variables​

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

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

model_config : The type of the None singleton.

ChannelMessagesSearchResult(**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.slack.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

ChannelsSearchResult(**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.slack.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

ThreadsSearchResult(**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.slack.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

UsersSearchResult(**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.slack.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

ChannelMessagesSearchData(**data: Any) : Search result data for channel_messages 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​

attachments: list[typing.Any] | None : Message attachments.

blocks: list[typing.Any] | None : Block kit blocks.

bot_id: str | None : Bot ID if message was sent by a bot.

bot_profile: dict[str, typing.Any] | None : Bot profile information.

is_locked: bool | None : Whether the thread is locked.

latest_reply: str | None : Timestamp of latest reply.

model_config : The type of the None singleton.

reactions: list[typing.Any] | None : Reactions to the message.

reply_count: int | None : Number of replies in thread.

reply_users: list[typing.Any] | None : User IDs who replied to the thread.

reply_users_count: int | None : Number of unique users who replied.

subscribed: bool | None : Whether the user is subscribed to the thread.

subtype: str | None : Message subtype.

team: str | None : Team ID.

text: str | None : Message text content.

thread_ts: str | None : Thread parent timestamp.

ts: str | None : Message timestamp (unique identifier).

type_: str | None : Message type.

user: str | None : User ID who sent the message.

ChannelsSearchData(**data: Any) : Search result data for channels 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​

context_team_id: str | None : The unique identifier of the team context in which the channel exists.

created: int | None : The timestamp when the channel was created.

creator: str | None : The ID of the user who created the channel.

id: str | None : The unique identifier of the channel.

is_archived: bool | None : Indicates if the channel is archived.

is_channel: bool | None : Indicates if the entity is a channel.

is_ext_shared: bool | None : Indicates if the channel is externally shared.

is_general: bool | None : Indicates if the channel is a general channel in the workspace.

is_group: bool | None : Indicates if the channel is a group (private channel) rather than a regular channel.

is_im: bool | None : Indicates if the entity is a direct message (IM) channel.

is_member: bool | None : Indicates if the calling user is a member of the channel.

is_mpim: bool | None : Indicates if the entity is a multiple person direct message (MPIM) channel.

is_org_shared: bool | None : Indicates if the channel is organization-wide shared.

is_pending_ext_shared: bool | None : Indicates if the channel is pending external shared.

is_private: bool | None : Indicates if the channel is a private channel.

is_read_only: bool | None : Indicates if the channel is read-only.

is_shared: bool | None : Indicates if the channel is shared.

last_read: str | None : The timestamp of the user's last read message in the channel.

locale: str | None : The locale of the channel.

model_config : The type of the None singleton.

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

name_normalized: str | None : The normalized name of the channel.

num_members: int | None : The number of members in the channel.

parent_conversation: str | None : The parent conversation of the channel.

pending_connected_team_ids: list[typing.Any] | None : The IDs of teams that are pending to be connected to the channel.

pending_shared: list[typing.Any] | None : The list of pending shared items of the channel.

previous_names: list[typing.Any] | None : The previous names of the channel.

purpose: dict[str, typing.Any] | None : The purpose of the channel.

shared_team_ids: list[typing.Any] | None : The IDs of teams with which the channel is shared.

topic: dict[str, typing.Any] | None : The topic of the channel.

unlinked: int | None : Indicates if the channel is unlinked.

updated: int | None : The timestamp when the channel was last updated.

SlackConnector(auth_config: SlackAuthConfig | AirbyteAuthConfig | BaseModel | None = None, on_token_refresh: Any | None = None) : Type-safe Slack API connector.

Auto-generated from OpenAPI specification with full type safety.

Initialize a new slack connector instance.

Supports both local and hosted execution modes:

  • Local mode: Provide connector-specific auth config (e.g., SlackAuthConfig)
  • 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 = SlackConnector(auth_config=SlackAuthConfig(bot_key="..."))

Hosted mode with explicit connector_id (no lookup needed)

connector = SlackConnector( 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 = SlackConnector( 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() @SlackConnector.tool_utils async def execute(entity: str, action: str, params: dict): ...

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

@mcp.tool() @SlackConnector.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.slack.models.SlackCheckResult : 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: SlackCheckResult 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', 'delete', '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']}")

SlackReplicationConfig(**data: Any) : Replication Configuration - Settings for data replication from Slack.

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​

include_archived_channels: bool : Whether to include archived channels in the sync. When disabled (default), archived channels are excluded from the Slack API response, reducing the number of API calls for downstream streams such as channel_messages, threads, and channel_members.

join_channels: bool : Whether to automatically join public channels to sync messages.

lookback_window: int : Number of days to look back when syncing data (0-365).

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.

threads_ignore_no_replies: bool : When enabled, the threads stream will skip messages that have no replies, reducing the number of API calls. Disabled by default to make the Threads stream contain unthreaded messages in its records.

ThreadsSearchData(**data: Any) : Search result data for threads 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​

blocks: list[typing.Any] | None : Block kit blocks.

bot_id: str | None : Bot ID if message was sent by a bot.

is_locked: bool | None : Whether the thread is locked.

latest_reply: str | None : Timestamp of latest reply.

model_config : The type of the None singleton.

parent_user_id: str | None : User ID of the parent message author (present in thread replies).

reply_count: int | None : Number of replies in thread.

reply_users: list[typing.Any] | None : User IDs who replied to the thread.

reply_users_count: int | None : Number of unique users who replied.

subscribed: bool | None : Whether the user is subscribed to the thread.

subtype: str | None : Message subtype.

team: str | None : Team ID.

text: str | None : Message text content.

thread_ts: str | None : Thread parent timestamp.

ts: str | None : Message timestamp (unique identifier).

type_: str | None : Message type.

user: str | None : User ID who sent the message.

UsersSearchData(**data: Any) : Search result data for users 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​

color: str | None : The color assigned to the user for visual purposes.

deleted: bool | None : Indicates if the user is deleted or not.

has_2fa: bool | None : Flag indicating if the user has two-factor authentication enabled.

id: str | None : Unique identifier for the user.

is_admin: bool | None : Flag specifying if the user is an admin or not.

is_app_user: bool | None : Specifies if the user is an app user.

is_bot: bool | None : Indicates if the user is a bot account.

is_email_confirmed: bool | None : Flag indicating if the user's email is confirmed.

is_forgotten: bool | None : Specifies if the user is marked as forgotten.

is_invited_user: bool | None : Indicates if the user is invited or not.

is_owner: bool | None : Flag indicating if the user is an owner.

is_primary_owner: bool | None : Specifies if the user is the primary owner.

is_restricted: bool | None : Flag specifying if the user is restricted.

is_ultra_restricted: bool | None : Indicates if the user has ultra-restricted access.

model_config : The type of the None singleton.

name: str | None : The username of the user.

profile: dict[str, typing.Any] | None : User's profile information containing detailed details.

real_name: str | None : The real name of the user.

team_id: str | None : Unique identifier for the team the user belongs to.

tz: str | None : Timezone of the user.

tz_label: str | None : Label representing the timezone of the user.

tz_offset: int | None : Offset of the user's timezone.

updated: int | None : Timestamp of when the user's information was last updated.

who_can_share_contact_card: str | None : Specifies who can share the user's contact card.

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