Module airbyte_agent_sdk.connectors.monday

Monday connector for Airbyte SDK.

Auto-generated from OpenAPI specification.

Sub-modules

airbyte_agent_sdk.connectors.monday.connector
airbyte_agent_sdk.connectors.monday.connector_model
airbyte_agent_sdk.connectors.monday.models
airbyte_agent_sdk.connectors.monday.types

Classes

ActivityLogsSearchData(**data: Any) : Search result data for activity_logs 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

board_id: int | None : Board ID the activity belongs to

created_at: str | None : When the activity occurred

created_at_int: int | None : When the activity occurred (Unix timestamp)

data: str | None : Event data (JSON string)

entity: str | None : Entity type that was affected

event: str | None : Event type

id: str | None : Unique activity log identifier

model_config : The type of the None singleton.

pulse_id: int | None : Item (pulse) ID the activity belongs to

user_id: str | None : ID of the user who performed the action

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.monday.models.AirbyteSearchResult[ActivityLogsSearchData]
airbyte_agent_sdk.connectors.monday.models.AirbyteSearchResult[BoardsSearchData]
airbyte_agent_sdk.connectors.monday.models.AirbyteSearchResult[ItemsSearchData]
airbyte_agent_sdk.connectors.monday.models.AirbyteSearchResult[TagsSearchData]
airbyte_agent_sdk.connectors.monday.models.AirbyteSearchResult[TeamsSearchData]
airbyte_agent_sdk.connectors.monday.models.AirbyteSearchResult[UpdatesSearchData]
airbyte_agent_sdk.connectors.monday.models.AirbyteSearchResult[UsersSearchData]
airbyte_agent_sdk.connectors.monday.models.AirbyteSearchResult[WorkspacesSearchData]

Class variables

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

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

model_config : The type of the None singleton.

ActivityLogsSearchResult(**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.monday.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

BoardsSearchResult(**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.monday.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

ItemsSearchResult(**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.monday.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

TagsSearchResult(**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.monday.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

TeamsSearchResult(**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.monday.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

UpdatesSearchResult(**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.monday.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.monday.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

WorkspacesSearchResult(**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.monday.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

BoardsSearchData(**data: Any) : Search result data for boards 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

board_kind: str | None : Board kind (public, private, share)

columns: list[typing.Any] | None : Board columns

communication: str | None : Board communication value

creator: dict[str, typing.Any] | None : Board creator

description: str | None : Board description

groups: list[typing.Any] | None : Board groups

id: str | None : Unique board identifier

model_config : The type of the None singleton.

name: str | None : Board name

owners: list[typing.Any] | None : Board owners

permissions: str | None : Board permissions

state: str | None : Board state (active, archived, deleted)

subscribers: list[typing.Any] | None : Board subscribers

tags: list[typing.Any] | None : Board tags

top_group: dict[str, typing.Any] | None : Top group on the board

type_: str | None : Board type

updated_at: str | None : When the board was last updated

updated_at_int: int | None : When the board was last updated (Unix timestamp)

updates: list[typing.Any] | None : Board updates

views: list[typing.Any] | None : Board views

workspace: dict[str, typing.Any] | None : Workspace the board belongs to

ItemsSearchData(**data: Any) : Search result data for items 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

assets: list[typing.Any] | None : Files attached to the item

board: dict[str, typing.Any] | None : Board the item belongs to

column_values: list[typing.Any] | None : Item column values

created_at: str | None : When the item was created

creator_id: str | None : ID of the user who created the item

group: dict[str, typing.Any] | None : Group the item belongs to

id: str | None : Unique item identifier

model_config : The type of the None singleton.

name: str | None : Item name

parent_item: dict[str, typing.Any] | None : Parent item (for subitems)

state: str | None : Item state (active, archived, deleted)

subscribers: list[typing.Any] | None : Item subscribers

updated_at: str | None : When the item was last updated

updated_at_int: int | None : When the item was last updated (Unix timestamp)

updates: list[typing.Any] | None : Item updates

MondayConnector(auth_config: MondayAuthConfig | AirbyteAuthConfig | BaseModel | None = None, on_token_refresh: Any | None = None) : Type-safe Monday API connector.

Auto-generated from OpenAPI specification with full type safety.

Initialize a new monday connector instance.

Supports both local and hosted execution modes:

Local mode: Provide connector-specific auth config (e.g., MondayAuthConfig)
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 = MondayConnector(auth_config=MondayAuthConfig(access_token="...", client_id="...", client_secret="..."))

Hosted mode with explicit connector_id (no lookup needed)

connector = MondayConnector( 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 = MondayConnector( 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: "'MondayAuthConfig' | None" = None, server_side_oauth_secret_id: str | None = None, name: str | None = None, replication_config: dict[str, Any] | 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

Supports two authentication modes:

Direct credentials: Provide auth_config with typed credentials
Server-side OAuth: Provide server_side_oauth_secret_id from OAuth flow

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. Required unless using server_side_oauth_secret_id. server_side_oauth_secret_id: OAuth secret ID from get_consent_url redirect. When provided, auth_config is not required. 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 MondayConnector instance configured in hosted mode

Raises: ValueError: If neither or both auth_config and server_side_oauth_secret_id provided

Example:

Create a new hosted connector with API key auth

connector = await MondayConnector.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=MondayAuthConfig(access_token="...", client_id="...", client_secret="..."), )

With server-side OAuth:

connector = await MondayConnector.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", ), server_side_oauth_secret_id="airbyte_oauth_...secret...", )

Use the connector

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

get_consent_url(*, airbyte_config: AirbyteAuthConfig, redirect_url: str, name: str | None = None, replication_config: dict[str, Any] | None = None, source_template_id: str | None = None) ‑> str : Initiate server-side OAuth flow with auto-source creation.

Returns a consent URL where the end user should be redirected to grant access. After completing consent, the source is automatically created and the user is redirected to your redirect_url with a connector_id query parameter.

Args: airbyte_config: Airbyte hosted auth config with client credentials and workspace_name. Optionally include organization_id for multi-org request routing. redirect_url: URL where users will be redirected after OAuth consent. After consent, user arrives at: redirect_url?connector_id=... name: Optional name for the source. Defaults to connector name + workspace_name. replication_config: Optional replication settings dict. Merged with OAuth credentials. source_template_id: Source template ID. Required when organization has multiple source templates for this connector type.

Returns: The OAuth consent URL

Example: consent_url = await MondayConnector.get_consent_url( airbyte_config=AirbyteAuthConfig( workspace_name="my-workspace", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc", airbyte_client_secret="secret_xyz", ), redirect_url="https://myapp.com/oauth/callback", name="My Monday Source", )

Redirect user to: consent_url

After consent, user arrives at: https://myapp.com/oauth/callback?connector_id=...

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

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

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

Methods

check(self) ‑> airbyte_agent_sdk.connectors.monday.models.MondayCheckResult : 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: MondayCheckResult 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']}")

TagsSearchData(**data: Any) : Search result data for tags 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 : Tag color

id: str | None : Unique tag identifier

model_config : The type of the None singleton.

name: str | None : Tag name

TeamsSearchData(**data: Any) : Search result data for teams 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

id: int | None : Unique team identifier

model_config : The type of the None singleton.

name: str | None : Team name

picture_url: str | None : Team picture URL

users: list[typing.Any] | None : Team members

UpdatesSearchData(**data: Any) : Search result data for updates 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

assets: list[typing.Any] | None : Files attached to this update

body: str | None : Update body (HTML)

created_at: str | None : When the update was created

creator_id: str | None : ID of the user who created the update

id: str | None : Unique update identifier

item_id: str | None : ID of the item this update belongs to

model_config : The type of the None singleton.

replies: list[typing.Any] | None : Replies to this update

text_body: str | None : Update body (plain text)

updated_at: str | None : When the update was last modified

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

birthday: str | None : User's birthday

country_code: str | None : User's country code

created_at: str | None : When the user was created

email: str | None : User's email address

enabled: bool | None : Whether the user account is enabled

id: str | None : Unique user identifier

is_admin: bool | None : Whether the user is an admin

is_guest: bool | None : Whether the user is a guest

is_pending: bool | None : Whether the user is pending

is_verified: bool | None : Whether the user is verified

is_view_only: bool | None : Whether the user is view-only

join_date: str | None : When the user joined

location: str | None : User's location

mobile_phone: str | None : User's mobile phone number

model_config : The type of the None singleton.

name: str | None : User's display name

phone: str | None : User's phone number

photo_original: str | None : URL to original size photo

photo_small: str | None : URL to small photo

photo_thumb: str | None : URL to thumbnail photo

photo_thumb_small: str | None : URL to small thumbnail photo

photo_tiny: str | None : URL to tiny photo

time_zone_identifier: str | None : User's timezone identifier

title: str | None : User's job title

url: str | None : User's Monday.com profile URL

utc_hours_diff: int | None : UTC hours difference for the user's timezone

WorkspacesSearchData(**data: Any) : Search result data for workspaces 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

account_product: dict[str, typing.Any] | None : Account product info

created_at: str | None : When the workspace was created

description: str | None : Workspace description

id: str | None : Unique workspace identifier

kind: str | None : Workspace kind (open, closed)

model_config : The type of the None singleton.

name: str | None : Workspace name

owners_subscribers: list[typing.Any] | None : Owner subscribers

settings: dict[str, typing.Any] | None : Workspace settings

state: str | None : Workspace state

team_owners_subscribers: list[typing.Any] | None : Team owner subscribers

teams_subscribers: list[typing.Any] | None : Team subscribers

users_subscribers: list[typing.Any] | None : User subscribers

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Hosted mode with connector_id (no lookup needed)

Hosted mode with workspace_name (lookup by workspace)

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Hosted mode with explicit connector_id (no lookup needed)

Hosted mode with lookup by workspace_name

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Create a new hosted connector with API key auth

With server-side OAuth:

Use the connector

Redirect user to: consent_url

After consent, user arrives at: https://myapp.com/oauth/callback?connector_id=...

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