Module airbyte_agent_sdk.connectors.snapchat_marketing.connector

Snapchat-Marketing connector.

Classes

AdaccountsQuery(connector: SnapchatMarketingConnector) : Query class for Adaccounts entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: AdaccountsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.AirbyteSearchResult[AdaccountsSearchData] : Search adaccounts records from Airbyte cache.

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

Available filter fields (AdaccountsSearchFilter):

advertiser_organization_id: Advertiser organization ID
agency_representing_client: Whether the account is managed by an agency
billing_center_id: Billing center ID
billing_type: Billing type
client_paying_invoices: Whether the client pays invoices directly
created_at: Creation timestamp
currency: Account currency code
funding_source_ids: Associated funding source IDs
id: Unique ad account identifier
name: Ad account name
organization_id: Parent organization ID
regulations: Regulatory settings
status: Ad account status
timezone: Account timezone
type_: Ad account type
updated_at: Last update timestamp

Args: query: Filter and sort conditions. Supports operators such as eq, neq, gt, gte, lt, lte, in, startswith, endswith, contains, array_contains, 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: AdaccountsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

context_store_sql_query(self, sql: str, limit: int | None = None) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.AirbyteSearchResult[dict[str, Any]] : Run a SQL query against adaccounts records in the Airbyte Context Store.

Only available in hosted execution mode.

Args: sql: SQL query to execute. limit: Maximum results to return.

Returns: AirbyteSearchResult containing the projected rows and query metadata.

Raises: NotImplementedError: If called in local execution mode.

get(self, id: str | None = None, **kwargs) ‑> dict[str, typing.Any] : Get a single ad account by ID

Args: id: Ad Account ID **kwargs: Additional parameters

Returns: dict[str, Any]

list(self, organization_id: str, **kwargs) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.SnapchatMarketingExecuteResultWithMeta[list[AdAccount], AdaccountsListResultMeta] : Returns ad accounts belonging to an organization

Args: organization_id: Organization ID **kwargs: Additional parameters

Returns: AdaccountsListResult

AdsQuery(connector: SnapchatMarketingConnector) : Query class for Ads entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: AdsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.AirbyteSearchResult[AdsSearchData] : Search ads records from Airbyte cache.

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

Available filter fields (AdsSearchFilter):

ad_squad_id: Parent ad squad ID
created_at: Creation timestamp
creative_id: Associated creative ID
delivery_status: Delivery status messages
id: Unique ad identifier
name: Ad name
render_type: Render type
review_status: Review status
review_status_reasons: Reasons for review status
status: Ad status
type_: Ad type
updated_at: Last update timestamp

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

Raises: NotImplementedError: If called in local execution mode

Only available in hosted execution mode.

Args: sql: SQL query to execute. limit: Maximum results to return.

Returns: AirbyteSearchResult containing the projected rows and query metadata.

Raises: NotImplementedError: If called in local execution mode.

get(self, id: str | None = None, **kwargs) ‑> dict[str, typing.Any] : Get a single ad by ID

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

Returns: dict[str, Any]

list(self, ad_account_id: str, **kwargs) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.SnapchatMarketingExecuteResultWithMeta[list[Ad], AdsListResultMeta] : Returns ads belonging to an ad account

Args: ad_account_id: Ad Account ID **kwargs: Additional parameters

Returns: AdsListResult

AdsquadsQuery(connector: SnapchatMarketingConnector) : Query class for Adsquads entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: AdsquadsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.AirbyteSearchResult[AdsquadsSearchData] : Search adsquads records from Airbyte cache.

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

Available filter fields (AdsquadsSearchFilter):

auto_bid: Whether auto bidding is enabled
bid_strategy: Bid strategy
billing_event: Billing event type
campaign_id: Parent campaign ID
child_ad_type: Child ad type
created_at: Creation timestamp
creation_state: Creation state
daily_budget_micro: Daily budget in micro-currency
delivery_constraint: Delivery constraint
delivery_properties_version: Delivery properties version
delivery_status: Delivery status messages
end_time: Ad squad end time
event_sources: Event sources configuration
forced_view_setting: Forced view setting
id: Unique ad squad identifier
lifetime_budget_micro: Lifetime budget in micro-currency
name: Ad squad name
optimization_goal: Optimization goal
pacing_type: Pacing type
placement: Placement type
skadnetwork_properties: SKAdNetwork properties
start_time: Ad squad start time
status: Ad squad status
target_bid: Whether target bid is enabled
targeting: Targeting specification
targeting_reach_status: Targeting reach status
type_: Ad squad type
updated_at: Last update timestamp

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

Raises: NotImplementedError: If called in local execution mode

Only available in hosted execution mode.

Args: sql: SQL query to execute. limit: Maximum results to return.

Returns: AirbyteSearchResult containing the projected rows and query metadata.

Raises: NotImplementedError: If called in local execution mode.

get(self, id: str | None = None, **kwargs) ‑> dict[str, typing.Any] : Get a single ad squad by ID

Args: id: Ad Squad ID **kwargs: Additional parameters

Returns: dict[str, Any]

list(self, ad_account_id: str, **kwargs) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.SnapchatMarketingExecuteResultWithMeta[list[AdSquad], AdsquadsListResultMeta] : Returns ad squads belonging to an ad account

Args: ad_account_id: Ad Account ID **kwargs: Additional parameters

Returns: AdsquadsListResult

CampaignsQuery(connector: SnapchatMarketingConnector) : Query class for Campaigns entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: CampaignsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.AirbyteSearchResult[CampaignsSearchData] : Search campaigns records from Airbyte cache.

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

Available filter fields (CampaignsSearchFilter):

ad_account_id: Parent ad account ID
buy_model: Buy model type
created_at: Creation timestamp
creation_state: Creation state
delivery_status: Delivery status messages
id: Unique campaign identifier
name: Campaign name
objective: Campaign objective
start_time: Campaign start time
status: Campaign status
updated_at: Last update timestamp

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

Raises: NotImplementedError: If called in local execution mode

Only available in hosted execution mode.

Args: sql: SQL query to execute. limit: Maximum results to return.

Returns: AirbyteSearchResult containing the projected rows and query metadata.

Raises: NotImplementedError: If called in local execution mode.

get(self, id: str | None = None, **kwargs) ‑> dict[str, typing.Any] : Get a single campaign by ID

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

Returns: dict[str, Any]

list(self, ad_account_id: str, **kwargs) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.SnapchatMarketingExecuteResultWithMeta[list[Campaign], CampaignsListResultMeta] : Returns campaigns belonging to an ad account

Args: ad_account_id: Ad Account ID **kwargs: Additional parameters

Returns: CampaignsListResult

CreativesQuery(connector: SnapchatMarketingConnector) : Query class for Creatives entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: CreativesSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.AirbyteSearchResult[CreativesSearchData] : Search creatives records from Airbyte cache.

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

Available filter fields (CreativesSearchFilter):

ad_account_id: Parent ad account ID
ad_product: Ad product type
ad_to_place_properties: Ad-to-place properties
brand_name: Brand name displayed in the creative
call_to_action: Call to action text
created_at: Creation timestamp
forced_view_eligibility: Forced view eligibility status
headline: Creative headline
id: Unique creative identifier
name: Creative name
packaging_status: Packaging status
render_type: Render type
review_status: Review status
review_status_details: Details about the review status
shareable: Whether the creative is shareable
top_snap_crop_position: Top snap crop position
top_snap_media_id: Top snap media ID
type_: Creative type
updated_at: Last update timestamp
web_view_properties: Web view properties

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

Raises: NotImplementedError: If called in local execution mode

Only available in hosted execution mode.

Args: sql: SQL query to execute. limit: Maximum results to return.

Returns: AirbyteSearchResult containing the projected rows and query metadata.

Raises: NotImplementedError: If called in local execution mode.

get(self, id: str | None = None, **kwargs) ‑> dict[str, typing.Any] : Get a single creative by ID

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

Returns: dict[str, Any]

list(self, ad_account_id: str, **kwargs) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.SnapchatMarketingExecuteResultWithMeta[list[Creative], CreativesListResultMeta] : Returns creatives belonging to an ad account

Args: ad_account_id: Ad Account ID **kwargs: Additional parameters

Returns: CreativesListResult

MediaQuery(connector: SnapchatMarketingConnector) : Query class for Media entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: MediaSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.AirbyteSearchResult[MediaSearchData] : Search media records from Airbyte cache.

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

Available filter fields (MediaSearchFilter):

ad_account_id: Parent ad account ID
created_at: Creation timestamp
download_link: Download URL for the media
duration_in_seconds: Duration in seconds for video media
file_name: Original file name
file_size_in_bytes: File size in bytes
hash: Media file hash
id: Unique media identifier
image_metadata: Image-specific metadata
is_demo_media: Whether this is demo media
media_status: Media processing status
media_usages: Where the media is used
name: Media name
type_: Media type
updated_at: Last update timestamp
video_metadata: Video-specific metadata
visibility: Media visibility setting

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

Raises: NotImplementedError: If called in local execution mode

Only available in hosted execution mode.

Args: sql: SQL query to execute. limit: Maximum results to return.

Returns: AirbyteSearchResult containing the projected rows and query metadata.

Raises: NotImplementedError: If called in local execution mode.

get(self, id: str | None = None, **kwargs) ‑> dict[str, typing.Any] : Get a single media item by ID

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

Returns: dict[str, Any]

list(self, ad_account_id: str, **kwargs) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.SnapchatMarketingExecuteResultWithMeta[list[Media], MediaListResultMeta] : Returns media belonging to an ad account

Args: ad_account_id: Ad Account ID **kwargs: Additional parameters

Returns: MediaListResult

OrganizationsQuery(connector: SnapchatMarketingConnector) : Query class for Organizations entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: OrganizationsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.AirbyteSearchResult[OrganizationsSearchData] : Search organizations records from Airbyte cache.

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

Available filter fields (OrganizationsSearchFilter):

accepted_term_version: Version of accepted terms
address_line_1: Street address
administrative_district_level_1: State or province
configuration_settings: Organization configuration settings
contact_email: Contact email address
contact_name: Contact person name
contact_phone: Contact phone number
contact_phone_optin: Whether the contact opted in for phone communications
country: Country code
created_by_caller: Whether the organization was created by the caller
created_at: Creation timestamp
id: Unique organization identifier
locality: City or locality
my_display_name: Display name of the authenticated user in the organization
my_invited_email: Email used to invite the authenticated user
my_member_id: Member ID of the authenticated user
name: Organization name
postal_code: Postal code
roles: Roles of the authenticated user in this organization
state: Organization state
type_: Organization type
updated_at: Last update timestamp

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

Raises: NotImplementedError: If called in local execution mode

Only available in hosted execution mode.

Args: sql: SQL query to execute. limit: Maximum results to return.

Returns: AirbyteSearchResult containing the projected rows and query metadata.

Raises: NotImplementedError: If called in local execution mode.

get(self, id: str | None = None, **kwargs) ‑> dict[str, typing.Any] : Get a single organization by ID

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

Returns: dict[str, Any]

list(self, **kwargs) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.SnapchatMarketingExecuteResultWithMeta[list[Organization], OrganizationsListResultMeta] : Returns the organizations the authenticated user belongs to

Returns: OrganizationsListResult

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

Initialize query with connector reference.

Methods

context_store_search(self, query: SegmentsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.AirbyteSearchResult[SegmentsSearchData] : Search segments records from Airbyte cache.

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

Available filter fields (SegmentsSearchFilter):

ad_account_id: Parent ad account ID
approximate_number_users: Approximate number of users in the segment
created_at: Creation timestamp
description: Segment description
id: Unique segment identifier
name: Segment name
organization_id: Parent organization ID
retention_in_days: Data retention period in days
source_type: Segment source type
status: Segment status
targetable_status: Whether the segment is targetable
updated_at: Last update timestamp
upload_status: Upload processing status
visible_to: Visibility settings

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

Raises: NotImplementedError: If called in local execution mode

Only available in hosted execution mode.

Args: sql: SQL query to execute. limit: Maximum results to return.

Returns: AirbyteSearchResult containing the projected rows and query metadata.

Raises: NotImplementedError: If called in local execution mode.

get(self, id: str | None = None, **kwargs) ‑> dict[str, typing.Any] : Get a single audience segment by ID

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

Returns: dict[str, Any]

list(self, ad_account_id: str, **kwargs) ‑> airbyte_agent_sdk.connectors.snapchat_marketing.models.SnapchatMarketingExecuteResultWithMeta[list[Segment], SegmentsListResultMeta] : Returns audience segments belonging to an ad account

Args: ad_account_id: Ad Account ID **kwargs: Additional parameters

Returns: SegmentsListResult

SnapchatMarketingConnector(auth_config: SnapchatMarketingAuthConfig | AirbyteAuthConfig | BaseModel | None = None, on_token_refresh: Any | None = None) : Type-safe Snapchat-Marketing API connector.

Auto-generated from OpenAPI specification with full type safety.

Initialize a new snapchat-marketing connector instance.

Supports both local and hosted execution modes:

Local mode: Provide connector-specific auth config (e.g., SnapchatMarketingAuthConfig)
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 = SnapchatMarketingConnector(auth_config=SnapchatMarketingAuthConfig(client_id="...", client_secret="...", refresh_token="..."))

Hosted mode with explicit connector_id (no lookup needed)

connector = SnapchatMarketingConnector( 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 = SnapchatMarketingConnector( 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

agent_tool(role: AgentToolRole | None = None, *, inspect_tool: str | None = None, docs_tool: str | None = None, max_output_chars: int | None | Unset = UNSET, framework: FrameworkName = '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) ‑> Callable[[~_F], ~_F] : Decorator for new user-written connector tool functions.

Use this when a tool needs a custom body or the framework lacks a native strategy. Instead of baking the full entity/action reference into the docstring, it instructs the agent to call this connector's inspect and docs tools before executing. Tool failures raise :class:airbyte_agent_sdk.AirbyteToolError by default (framework="none", no auto-detection) — pass framework=... to translate to a supported framework's signal instead.

Decorate three functions per connector — execute, inspect and docs. The role is inferred from each function's signature (extra parameters are allowed); a signature matching more than one role, a generic (*args, **kwargs) wrapper, or a callable whose signature cannot be read must pass the role explicitly:

(entity, action, ...) -> "execute"
(section, ...) -> "read_skill_docs"
() -> "inspect_connector"

Usage: connector = SnapchatMarketingConnector(...)

@SnapchatMarketingConnector.agent_tool() async def execute(entity: str, action: str, params: dict | None = None): return await connector.execute(entity=entity, action=action, params=params or {})

@SnapchatMarketingConnector.agent_tool() async def inspect_connector(): return await connector.inspect_connector()

@SnapchatMarketingConnector.agent_tool() async def read_skill_docs(section: str | None = None): return await connector.read_skill_docs(section)

Args: role: "execute" | "inspect_connector" | "read_skill_docs". None (default) infers the role from the decorated function's signature; an explicit role validates the canonical parameters are present (functions accepting **kwargs, or callables whose signature cannot be read, pass validation). inspect_tool: Exact registered name of the sibling inspect tool, woven into the execute docstring for tighter steering. Defaults to generic phrasing. docs_tool: Exact registered name of the sibling docs tool (see inspect_tool). max_output_chars: Max serialized output size before failing. Defaults per role: execute -> DEFAULT_MAX_OUTPUT_CHARS, docs tools -> None. framework: Translation target for tool failures. Defaults to "none" (raise AirbyteToolError); never auto-detects. internal_retries: How many transient runtime failures (429/5xx, network, timeout) to retry silently before surfacing. 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 skipped. Forwarded to :func:airbyte_agent_sdk.translation.translate_exceptions.

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] : Deprecated. Add connector-specific documentation and runtime safeguards to one tool.

Kept for backwards compatibility with existing single-tool integrations; it is not removed and does not warn at runtime, but new code should use build_connector_tools or agent_tool below.

For new agents, prefer build_connector_tools. It returns progressive inspect_connector, read_skill_docs, and execute tools so the agent can load only the connector guidance it needs:

from airbyte_agent_sdk import build_connector_tools
from pydantic_ai import Agent

tools = build_connector_tools(connector, framework="pydantic_ai")
agent = Agent("openai:gpt-4o", tools=tools.as_list())

When a new integration needs custom tool bodies or a framework without native support, use agent_tool instead.

Legacy: one generated-description tool

Existing integrations can keep using tool_utils for one broad execute tool with the connector's full generated catalog in its description:

from fastmcp import FastMCP

connector = SnapchatMarketingConnector()
mcp = FastMCP("Connector Agent")

@mcp.tool()
@SnapchatMarketingConnector.tool_utils
async def execute(entity: str, action: str, params: dict):
    ...

Configure documentation, output limits, framework translation, and retries when needed:

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

@mcp.tool()
@SnapchatMarketingConnector.tool_utils(framework="pydantic_ai", internal_retries=2)
async def execute(entity: str, action: str, params: dict):
    ...

This decorator composes translate_exceptions for runtime wrapping, output-size checks, framework signal translation, and optional internal retries, then adds connector-specific docstring augmentation.

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" | "none". Defaults to None, which auto-detects each framework's canonical import in order and falls back to "none" with a warning when no supported framework is installed. Explicit always wins, and an explicit framework whose package is missing raises RuntimeError. internal_retries: How many transient runtime failures (429/5xx, network, timeout) to retry silently before surfacing. Default 0. Forwarded to 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 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 because should_internal_retry returned False. Forwarded to 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.snapchat_marketing.models.SnapchatMarketingCheckResult : 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: SnapchatMarketingCheckResult 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', 'context_store_sql_query']", params: Mapping[str, Any] | None = None, *, select_fields: list[str] | None = None, exclude_fields: list[str] | None = None, skip_truncation: bool = True) ‑> 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) select_fields: Optional allowlist of dot-notation fields to include exclude_fields: Optional blocklist of dot-notation fields to remove skip_truncation: Disable long-text truncation for collection actions

Returns: Typed response based on the operation

Example: customer = await connector.execute( entity="customers", action="get", params={"id": "cus_123"} )

inspect_connector(self) ‑> dict[str, typing.Any] : Inspect this connector's hosted metadata/readiness and resolve its docs skill id.

Call this before read_skill_docs in the normal hosted flow. For local/offline connectors this returns a local-mode payload with a warning instead of a hosted inspection.

Example: info = await connector.inspect_connector() print(info["docs_skill_id"])

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']}")

read_skill_docs(self, section: str | None = None) ‑> str : Read this connector's usage docs, rendered to text.

Omit section for the outline and general guidance; pass an exact section id from the outline for full details. For local/offline connectors the full generated docs are returned and section is ignored.

Example: outline = await connector.read_skill_docs() details = await connector.read_skill_docs(section="entity:contacts")

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​

Legacy: one generated-description tool​

Instance variables​

Methods​

Classes

Methods

Methods

Methods

Methods

Methods

Methods

Methods

Methods

Class variables

Static methods

Legacy: one generated-description tool

Instance variables

Methods