Module airbyte_agent_sdk.connectors.greenhouse.connector

Greenhouse connector.

Classes

ApplicationAttachmentQuery(connector: GreenhouseConnector) : Query class for ApplicationAttachment entity operations.

Initialize query with connector reference.

Methods

download(self, attachment_index: str, id: str | None = None, range_header: str | None = None, **kwargs) ‑> AsyncIterator[bytes] : Downloads an attachment (resume, cover letter, etc.) for an application by index. The attachment URL is a temporary signed AWS S3 URL that expires within 7 days. Files should be downloaded immediately after retrieval.

Args: id: Application ID attachment_index: Index of the attachment to download (0-based) range_header: Optional Range header for partial downloads (e.g., 'bytes=0-99') **kwargs: Additional parameters

Returns: AsyncIterator[bytes]

download_local(self, attachment_index: str, path: str, id: str | None = None, range_header: str | None = None, **kwargs) ‑> Path : Downloads an attachment (resume, cover letter, etc.) for an application by index. The attachment URL is a temporary signed AWS S3 URL that expires within 7 days. Files should be downloaded immediately after retrieval. and save to file.

Args: id: Application ID attachment_index: Index of the attachment to download (0-based) range_header: Optional Range header for partial downloads (e.g., 'bytes=0-99') path: File path to save downloaded content **kwargs: Additional parameters

Returns: str: Path to the downloaded file

ApplicationsQuery(connector: GreenhouseConnector) : Query class for Applications entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: ApplicationsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.greenhouse.models.AirbyteSearchResult[ApplicationsSearchData] : Search applications records from Airbyte cache.

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

Available filter fields (ApplicationsSearchFilter):

answers: Answers provided in the application.
applied_at: Timestamp when the candidate applied.
attachments: Attachments uploaded with the application.
candidate_id: Unique identifier for the candidate.
credited_to: Information about the employee who credited the application.
current_stage: Current stage of the application process.
id: Unique identifier for the application.
job_post_id:
jobs: Jobs applied for by the candidate.
last_activity_at: Timestamp of the last activity on the application.
location: Location related to the application.
prospect: Status of the application prospect.
prospect_detail: Details related to the application prospect.
prospective_department: Prospective department for the candidate.
prospective_office: Prospective office for the candidate.
rejected_at: Timestamp when the application was rejected.
rejection_details: Details related to the application rejection.
rejection_reason: Reason for the application rejection.
source: Source of the application.
status: Status of the application.

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: ApplicationsSearchResult 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.greenhouse.models.Application : Get a single application by ID

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

Returns: Application

list(self, per_page: int | None = None, page: int | None = None, created_before: str | None = None, created_after: str | None = None, last_activity_after: str | None = None, job_id: int | None = None, status: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.greenhouse.models.GreenhouseExecuteResultWithMeta[list[Application], ApplicationsListResultMeta] : Returns a paginated list of all applications

Args: per_page: Number of items to return per page (max 500) page: Page number for pagination created_before: Filter by applications created before this timestamp created_after: Filter by applications created after this timestamp last_activity_after: Filter by applications with activity after this timestamp job_id: Filter by job ID status: Filter by application status **kwargs: Additional parameters

Returns: ApplicationsListResult

CandidateAttachmentQuery(connector: GreenhouseConnector) : Query class for CandidateAttachment entity operations.

Initialize query with connector reference.

Methods

download(self, attachment_index: str, id: str | None = None, range_header: str | None = None, **kwargs) ‑> AsyncIterator[bytes] : Downloads an attachment (resume, cover letter, etc.) for a candidate by index. The attachment URL is a temporary signed AWS S3 URL that expires within 7 days. Files should be downloaded immediately after retrieval.

Args: id: Candidate ID attachment_index: Index of the attachment to download (0-based) range_header: Optional Range header for partial downloads (e.g., 'bytes=0-99') **kwargs: Additional parameters

Returns: AsyncIterator[bytes]

download_local(self, attachment_index: str, path: str, id: str | None = None, range_header: str | None = None, **kwargs) ‑> Path : Downloads an attachment (resume, cover letter, etc.) for a candidate by index. The attachment URL is a temporary signed AWS S3 URL that expires within 7 days. Files should be downloaded immediately after retrieval. and save to file.

Args: id: Candidate ID attachment_index: Index of the attachment to download (0-based) range_header: Optional Range header for partial downloads (e.g., 'bytes=0-99') path: File path to save downloaded content **kwargs: Additional parameters

Returns: str: Path to the downloaded file

CandidatesQuery(connector: GreenhouseConnector) : Query class for Candidates entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: CandidatesSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.greenhouse.models.AirbyteSearchResult[CandidatesSearchData] : Search candidates records from Airbyte cache.

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

Available filter fields (CandidatesSearchFilter):

addresses: Candidate's addresses
application_ids: List of application IDs
applications: An array of all applications made by candidates.
attachments: Attachments related to the candidate
can_email: Indicates if candidate can be emailed
company: Company where the candidate is associated
coordinator: Coordinator assigned to the candidate
created_at: Date and time of creation
custom_fields: Custom fields associated with the candidate
educations: List of candidate's educations
email_addresses: Candidate's email addresses
employments: List of candidate's employments
first_name: Candidate's first name
id: Candidate's ID
is_private: Indicates if the candidate's data is private
keyed_custom_fields: Keyed custom fields associated with the candidate
last_activity: Details of the last activity related to the candidate
last_name: Candidate's last name
phone_numbers: Candidate's phone numbers
photo_url: URL of the candidate's profile photo
recruiter: Recruiter assigned to the candidate
social_media_addresses: Candidate's social media addresses
tags: Tags associated with the candidate
title: Candidate's title (e.g., Mr., Mrs., Dr.)
updated_at: Date and time of last update
website_addresses: List of candidate's website addresses

Returns: CandidatesSearchResult 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.greenhouse.models.Candidate : Get a single candidate by ID

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

Returns: Candidate

list(self, per_page: int | None = None, page: int | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.greenhouse.models.GreenhouseExecuteResultWithMeta[list[Candidate], CandidatesListResultMeta] : Returns a paginated list of all candidates in the organization

Args: per_page: Number of items to return per page (max 500) page: Page number for pagination **kwargs: Additional parameters

Returns: CandidatesListResult

DepartmentsQuery(connector: GreenhouseConnector) : Query class for Departments entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: DepartmentsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.greenhouse.models.AirbyteSearchResult[DepartmentsSearchData] : Search departments records from Airbyte cache.

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

Available filter fields (DepartmentsSearchFilter):

child_department_external_ids: External IDs of child departments associated with this department.
child_ids: Unique IDs of child departments associated with this department.
external_id: External ID of this department.
id: Unique ID of this department.
name: Name of the department.
parent_department_external_id: External ID of the parent department of this department.
parent_id: Unique ID of the parent department of this department.

Returns: DepartmentsSearchResult 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.greenhouse.models.Department : Get a single department by ID

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

Returns: Department

list(self, per_page: int | None = None, page: int | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.greenhouse.models.GreenhouseExecuteResultWithMeta[list[Department], DepartmentsListResultMeta] : Returns a paginated list of all departments

Args: per_page: Number of items to return per page (max 500) page: Page number for pagination **kwargs: Additional parameters

Returns: DepartmentsListResult

GreenhouseConnector(auth_config: GreenhouseAuthConfig | AirbyteAuthConfig | BaseModel | None = None, on_token_refresh: Any | None = None) : Type-safe Greenhouse API connector.

Auto-generated from OpenAPI specification with full type safety.

Initialize a new greenhouse connector instance.

Supports both local and hosted execution modes:

Local mode: Provide connector-specific auth config (e.g., GreenhouseAuthConfig)
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 = GreenhouseConnector(auth_config=GreenhouseAuthConfig(api_key="..."))

Hosted mode with explicit connector_id (no lookup needed)

connector = GreenhouseConnector( 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 = GreenhouseConnector( 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: "'GreenhouseAuthConfig'", name: str | None = None, replication_config: dict[str, Any] | None = None, source_template_id: str | None = None) ‑> airbyte_agent_sdk.connectors.greenhouse.connector.GreenhouseConnector : 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: 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 GreenhouseConnector instance configured in hosted mode

Example:

Create a new hosted connector with API key auth

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

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

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

Methods

check(self) ‑> airbyte_agent_sdk.connectors.greenhouse.models.GreenhouseCheckResult : 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: GreenhouseCheckResult 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', 'download', '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']}")

JobPostsQuery(connector: GreenhouseConnector) : Query class for JobPosts entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: JobPostsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.greenhouse.models.AirbyteSearchResult[JobPostsSearchData] : Search job_posts records from Airbyte cache.

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

Available filter fields (JobPostsSearchFilter):

active: Flag indicating if the job post is active or not.
content: Content or description of the job post.
created_at: Date and time when the job post was created.
demographic_question_set_id: ID of the demographic question set associated with the job post.
external: Flag indicating if the job post is external or not.
first_published_at: Date and time when the job post was first published.
id: Unique identifier of the job post.
internal: Flag indicating if the job post is internal or not.
internal_content: Internal content or description of the job post.
job_id: ID of the job associated with the job post.
live: Flag indicating if the job post is live or not.
location: Details about the job post location.
questions: List of questions related to the job post.
title: Title or headline of the job post.
updated_at: Date and time when the job post was last updated.

Returns: JobPostsSearchResult 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.greenhouse.models.JobPost : Get a single job post by ID

Args: id: Job Post ID **kwargs: Additional parameters

Returns: JobPost

list(self, per_page: int | None = None, page: int | None = None, live: bool | None = None, active: bool | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.greenhouse.models.GreenhouseExecuteResultWithMeta[list[JobPost], JobPostsListResultMeta] : Returns a paginated list of all job posts

Args: per_page: Number of items to return per page (max 500) page: Page number for pagination live: Filter by live status active: Filter by active status **kwargs: Additional parameters

Returns: JobPostsListResult

JobsQuery(connector: GreenhouseConnector) : Query class for Jobs entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: JobsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.greenhouse.models.AirbyteSearchResult[JobsSearchData] : Search jobs records from Airbyte cache.

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

Available filter fields (JobsSearchFilter):

closed_at: The date and time the job was closed
confidential: Indicates if the job details are confidential
copied_from_id: The ID of the job from which this job was copied
created_at: The date and time the job was created
custom_fields: Custom fields related to the job
departments: Departments associated with the job
hiring_team: Members of the hiring team for the job
id: Unique ID of the job
is_template: Indicates if the job is a template
keyed_custom_fields: Keyed custom fields related to the job
name: Name of the job
notes: Additional notes or comments about the job
offices: Offices associated with the job
opened_at: The date and time the job was opened
openings: Openings associated with the job
requisition_id: ID associated with the job requisition
status: Current status of the job
updated_at: The date and time the job was last updated

Returns: JobsSearchResult 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.greenhouse.models.Job : Get a single job by ID

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

Returns: Job

list(self, per_page: int | None = None, page: int | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.greenhouse.models.GreenhouseExecuteResultWithMeta[list[Job], JobsListResultMeta] : Returns a paginated list of all jobs in the organization

Args: per_page: Number of items to return per page (max 500) page: Page number for pagination **kwargs: Additional parameters

Returns: JobsListResult

OffersQuery(connector: GreenhouseConnector) : Query class for Offers entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: OffersSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.greenhouse.models.AirbyteSearchResult[OffersSearchData] : Search offers records from Airbyte cache.

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

Available filter fields (OffersSearchFilter):

application_id: Unique identifier for the application associated with the offer
candidate_id: Unique identifier for the candidate associated with the offer
created_at: Timestamp indicating when the offer was created
custom_fields: Additional custom fields related to the offer
id: Unique identifier for the offer
job_id: Unique identifier for the job associated with the offer
keyed_custom_fields: Keyed custom fields associated with the offer
opening: Details about the job opening
resolved_at: Timestamp indicating when the offer was resolved
sent_at: Timestamp indicating when the offer was sent
starts_at: Timestamp indicating when the offer starts
status: Status of the offer
updated_at: Timestamp indicating when the offer was last updated
version: Version of the offer data

Returns: OffersSearchResult 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.greenhouse.models.Offer : Get a single offer by ID

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

Returns: Offer

list(self, per_page: int | None = None, page: int | None = None, created_before: str | None = None, created_after: str | None = None, resolved_after: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.greenhouse.models.GreenhouseExecuteResultWithMeta[list[Offer], OffersListResultMeta] : Returns a paginated list of all offers

Args: per_page: Number of items to return per page (max 500) page: Page number for pagination created_before: Filter by offers created before this timestamp created_after: Filter by offers created after this timestamp resolved_after: Filter by offers resolved after this timestamp **kwargs: Additional parameters

Returns: OffersListResult

OfficesQuery(connector: GreenhouseConnector) : Query class for Offices entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: OfficesSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.greenhouse.models.AirbyteSearchResult[OfficesSearchData] : Search offices records from Airbyte cache.

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

Available filter fields (OfficesSearchFilter):

child_ids: IDs of child offices associated with this office
child_office_external_ids: External IDs of child offices associated with this office
external_id: Unique identifier for this office in the external system
id: Unique identifier for this office in the API system
location: Location details of this office
name: Name of the office
parent_id: ID of the parent office, if this office is a branch office
parent_office_external_id: External ID of the parent office in the external system
primary_contact_user_id: User ID of the primary contact person for this office

Returns: OfficesSearchResult 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.greenhouse.models.Office : Get a single office by ID

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

Returns: Office

list(self, per_page: int | None = None, page: int | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.greenhouse.models.GreenhouseExecuteResultWithMeta[list[Office], OfficesListResultMeta] : Returns a paginated list of all offices

Args: per_page: Number of items to return per page (max 500) page: Page number for pagination **kwargs: Additional parameters

Returns: OfficesListResult

ScheduledInterviewsQuery(connector: GreenhouseConnector) : Query class for ScheduledInterviews entity operations.

Initialize query with connector reference.

Methods

get(self, id: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.greenhouse.models.ScheduledInterview : Get a single scheduled interview by ID

Args: id: Scheduled Interview ID **kwargs: Additional parameters

Returns: ScheduledInterview

list(self, per_page: int | None = None, page: int | None = None, created_before: str | None = None, created_after: str | None = None, updated_before: str | None = None, updated_after: str | None = None, starts_after: str | None = None, ends_before: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.greenhouse.models.GreenhouseExecuteResultWithMeta[list[ScheduledInterview], ScheduledInterviewsListResultMeta] : Returns a paginated list of all scheduled interviews

Args: per_page: Number of items to return per page (max 500) page: Page number for pagination created_before: Filter by interviews created before this timestamp created_after: Filter by interviews created after this timestamp updated_before: Filter by interviews updated before this timestamp updated_after: Filter by interviews updated after this timestamp starts_after: Filter by interviews starting after this timestamp ends_before: Filter by interviews ending before this timestamp **kwargs: Additional parameters

Returns: ScheduledInterviewsListResult

SourcesQuery(connector: GreenhouseConnector) : Query class for Sources entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: SourcesSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.greenhouse.models.AirbyteSearchResult[SourcesSearchData] : Search sources records from Airbyte cache.

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

Available filter fields (SourcesSearchFilter):

id: The unique identifier for the source.
name: The name of the source.
type_: Type of the data source

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

Raises: NotImplementedError: If called in local execution mode

list(self, per_page: int | None = None, page: int | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.greenhouse.models.GreenhouseExecuteResultWithMeta[list[Source], SourcesListResultMeta] : Returns a paginated list of all sources

Args: per_page: Number of items to return per page (max 500) page: Page number for pagination **kwargs: Additional parameters

Returns: SourcesListResult

UsersQuery(connector: GreenhouseConnector) : Query class for Users entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: UsersSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.greenhouse.models.AirbyteSearchResult[UsersSearchData] : Search users records from Airbyte cache.

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

Available filter fields (UsersSearchFilter):

created_at: The date and time when the user account was created.
departments: List of departments associated with users
disabled: Indicates whether the user account is disabled.
emails: Email addresses of the users
employee_id: Employee identifier for the user.
first_name: The first name of the user.
id: Unique identifier for the user.
last_name: The last name of the user.
linked_candidate_ids: IDs of candidates linked to the user.
name: The full name of the user.
offices: List of office locations where users are based
primary_email_address: The primary email address of the user.
site_admin: Indicates whether the user is a site administrator.
updated_at: The date and time when the user account was last updated.

Returns: UsersSearchResult 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.greenhouse.models.User : Get a single user by ID

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

Returns: User

list(self, per_page: int | None = None, page: int | None = None, created_before: str | None = None, created_after: str | None = None, updated_before: str | None = None, updated_after: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.greenhouse.models.GreenhouseExecuteResultWithMeta[list[User], UsersListResultMeta] : Returns a paginated list of all users

Args: per_page: Number of items to return per page (max 500) page: Page number for pagination created_before: Filter by users created before this timestamp created_after: Filter by users created after this timestamp updated_before: Filter by users updated before this timestamp updated_after: Filter by users updated after this timestamp **kwargs: Additional parameters

Returns: UsersListResult

Classes​

Methods​

Methods​

Methods​

Methods​

Methods​

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

Use the connector

Instance variables​

Methods​

Methods​

Methods​

Methods​

Methods​

Methods​

Methods​

Methods​

Classes

Methods

Methods

Methods

Methods

Methods

Class variables

Static methods

Instance variables

Methods

Methods

Methods

Methods

Methods

Methods

Methods

Methods