Module airbyte_agent_sdk.connectors.google_search_console.connector

Google-Search-Console connector.

Classes

GoogleSearchConsoleConnector(auth_config: GoogleSearchConsoleAuthConfig | AirbyteAuthConfig | BaseModel | None = None, on_token_refresh: Any | None = None) : Type-safe Google-Search-Console API connector.

Auto-generated from OpenAPI specification with full type safety.

Initialize a new google-search-console connector instance.

Supports both local and hosted execution modes:

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

Hosted mode with explicit connector_id (no lookup needed)

connector = GoogleSearchConsoleConnector( 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 = GoogleSearchConsoleConnector( 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 = GoogleSearchConsoleConnector(...)

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

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

@GoogleSearchConsoleConnector.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 = GoogleSearchConsoleConnector()
mcp = FastMCP("Connector Agent")

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

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

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

@mcp.tool()
@GoogleSearchConsoleConnector.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.google_search_console.models.GoogleSearchConsoleCheckResult : 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: GoogleSearchConsoleCheckResult 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")

SearchAnalyticsAllFieldsQuery(connector: GoogleSearchConsoleConnector) : Query class for SearchAnalyticsAllFields entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: SearchAnalyticsAllFieldsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.google_search_console.models.AirbyteSearchResult[SearchAnalyticsAllFieldsSearchData] : Search search_analytics_all_fields records from Airbyte cache.

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

Available filter fields (SearchAnalyticsAllFieldsSearchFilter):

clicks: The number of times users clicked on the search result for a specific query
country: The country from which the search query originated
ctr: Click-through rate, calculated as clicks divided by impressions
date: The date when the search query occurred
device: The type of device used by the user (e.g., desktop, mobile)
impressions: The number of times a search result appeared in response to a query
page: The page URL that appeared in the search results
position: The average position of the search result on the search engine results page
query: The search query entered by the user
search_type: The type of search (e.g., web, image, video) that triggered the search result
site_url: The URL of the site from which the data originates

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: SearchAnalyticsAllFieldsSearchResult 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.google_search_console.models.AirbyteSearchResult[dict[str, Any]] : Run a SQL query against search_analytics_all_fields 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.

list(self, start_date: str, end_date: str, site_url: str, dimensions: list[str] | None = None, row_limit: int | None = None, start_row: int | None = None, type: str | None = None, aggregation_type: str | None = None, data_state: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.google_search_console.models.GoogleSearchConsoleExecuteResultWithMeta[list[SearchAnalyticsRow], SearchAnalyticsAllFieldsListResultMeta] : Query search analytics data grouped by all dimensions (date, country, device, page, query). Returns the most granular breakdown of search data.

Args: start_date: Start date of the requested date range, in YYYY-MM-DD format. end_date: End date of the requested date range, in YYYY-MM-DD format. dimensions: Dimensions to group results by. row_limit: The maximum number of rows to return. start_row: Zero-based index of the first row in the response. type: Filter results by type: web, discover, googleNews, news, image, video.

aggregation_type: How data is aggregated: auto, byPage, byProperty.

data_state: Data freshness: final (stable data only) or all (includes fresh data).

site_url: The URL of the property as defined in Search Console. **kwargs: Additional parameters

Returns: SearchAnalyticsAllFieldsListResult

SearchAnalyticsByCountryQuery(connector: GoogleSearchConsoleConnector) : Query class for SearchAnalyticsByCountry entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: SearchAnalyticsByCountrySearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.google_search_console.models.AirbyteSearchResult[SearchAnalyticsByCountrySearchData] : Search search_analytics_by_country records from Airbyte cache.

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

Available filter fields (SearchAnalyticsByCountrySearchFilter):

clicks: The number of times users clicked on the search result for a specific country
country: The country for which the search analytics data is being reported
ctr: The click-through rate for a specific country
date: The date for which the search analytics data is being reported
impressions: The total number of times a search result was shown for a specific country
position: The average position at which the site's search result appeared for a specific country
search_type: The type of search for which the data is being reported
site_url: The URL of the site for which the search analytics data is being reported

Returns: SearchAnalyticsByCountrySearchResult 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.

list(self, start_date: str, end_date: str, site_url: str, dimensions: list[str] | None = None, row_limit: int | None = None, start_row: int | None = None, type: str | None = None, aggregation_type: str | None = None, data_state: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.google_search_console.models.GoogleSearchConsoleExecuteResultWithMeta[list[SearchAnalyticsRow], SearchAnalyticsByCountryListResultMeta] : Query search analytics data grouped by date and country. Returns clicks, impressions, CTR, and average position for each country.

aggregation_type: How data is aggregated: auto, byPage, byProperty.

data_state: Data freshness: final (stable data only) or all (includes fresh data).

site_url: The URL of the property as defined in Search Console. **kwargs: Additional parameters

Returns: SearchAnalyticsByCountryListResult

SearchAnalyticsByDateQuery(connector: GoogleSearchConsoleConnector) : Query class for SearchAnalyticsByDate entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: SearchAnalyticsByDateSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.google_search_console.models.AirbyteSearchResult[SearchAnalyticsByDateSearchData] : Search search_analytics_by_date records from Airbyte cache.

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

Available filter fields (SearchAnalyticsByDateSearchFilter):

clicks: The total number of clicks on the specific date
ctr: The click-through rate for the specific date
date: The date for which the search analytics data is being reported
impressions: The number of impressions on the specific date
position: The average position in search results for the specific date
search_type: The type of search query that generated the data
site_url: The URL of the site for which the search analytics data is being reported

Returns: SearchAnalyticsByDateSearchResult 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.

list(self, start_date: str, end_date: str, site_url: str, dimensions: list[str] | None = None, row_limit: int | None = None, start_row: int | None = None, type: str | None = None, aggregation_type: str | None = None, data_state: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.google_search_console.models.GoogleSearchConsoleExecuteResultWithMeta[list[SearchAnalyticsRow], SearchAnalyticsByDateListResultMeta] : Query search analytics data grouped by date. Returns clicks, impressions, CTR, and average position for each date in the specified range.

aggregation_type: How data is aggregated: auto, byPage, byProperty, byNewsShowcasePanel.

data_state: Data freshness: final (stable data only) or all (includes fresh data).

site_url: The URL of the property as defined in Search Console. **kwargs: Additional parameters

Returns: SearchAnalyticsByDateListResult

SearchAnalyticsByDeviceQuery(connector: GoogleSearchConsoleConnector) : Query class for SearchAnalyticsByDevice entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: SearchAnalyticsByDeviceSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.google_search_console.models.AirbyteSearchResult[SearchAnalyticsByDeviceSearchData] : Search search_analytics_by_device records from Airbyte cache.

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

Available filter fields (SearchAnalyticsByDeviceSearchFilter):

clicks: The total number of clicks by device type
ctr: Click-through rate by device type
date: The date for which the search analytics data is provided
device: The type of device used by the user (e.g., desktop, mobile)
impressions: The total number of impressions by device type
position: The average position in search results by device type
search_type: The type of search performed
site_url: The URL of the site for which search analytics data is being provided

Returns: SearchAnalyticsByDeviceSearchResult 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.

list(self, start_date: str, end_date: str, site_url: str, dimensions: list[str] | None = None, row_limit: int | None = None, start_row: int | None = None, type: str | None = None, aggregation_type: str | None = None, data_state: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.google_search_console.models.GoogleSearchConsoleExecuteResultWithMeta[list[SearchAnalyticsRow], SearchAnalyticsByDeviceListResultMeta] : Query search analytics data grouped by date and device. Returns clicks, impressions, CTR, and average position for each device type.

aggregation_type: How data is aggregated: auto, byPage, byProperty.

data_state: Data freshness: final (stable data only) or all (includes fresh data).

site_url: The URL of the property as defined in Search Console. **kwargs: Additional parameters

Returns: SearchAnalyticsByDeviceListResult

SearchAnalyticsByPageQuery(connector: GoogleSearchConsoleConnector) : Query class for SearchAnalyticsByPage entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: SearchAnalyticsByPageSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.google_search_console.models.AirbyteSearchResult[SearchAnalyticsByPageSearchData] : Search search_analytics_by_page records from Airbyte cache.

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

Available filter fields (SearchAnalyticsByPageSearchFilter):

clicks: The number of clicks for a specific page
ctr: Click-through rate for the page
date: The date for which the search analytics data is reported
impressions: The number of impressions for the page
page: The URL of the specific page being analyzed
position: The average position at which the page appeared in search results
search_type: The type of search query that led to the page being displayed
site_url: The URL of the site for which the search analytics data is being reported

Returns: SearchAnalyticsByPageSearchResult 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.

list(self, start_date: str, end_date: str, site_url: str, dimensions: list[str] | None = None, row_limit: int | None = None, start_row: int | None = None, type: str | None = None, aggregation_type: str | None = None, data_state: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.google_search_console.models.GoogleSearchConsoleExecuteResultWithMeta[list[SearchAnalyticsRow], SearchAnalyticsByPageListResultMeta] : Query search analytics data grouped by date and page. Returns clicks, impressions, CTR, and average position for each page URL.

aggregation_type: How data is aggregated: auto, byPage, byProperty.

data_state: Data freshness: final (stable data only) or all (includes fresh data).

site_url: The URL of the property as defined in Search Console. **kwargs: Additional parameters

Returns: SearchAnalyticsByPageListResult

SearchAnalyticsByQueryQuery(connector: GoogleSearchConsoleConnector) : Query class for SearchAnalyticsByQuery entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: SearchAnalyticsByQuerySearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.google_search_console.models.AirbyteSearchResult[SearchAnalyticsByQuerySearchData] : Search search_analytics_by_query records from Airbyte cache.

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

Available filter fields (SearchAnalyticsByQuerySearchFilter):

clicks: The number of clicks for the specific query
ctr: The click-through rate for the specific query
date: The date for which the search analytics data is recorded
impressions: The number of impressions for the specific query
position: The average position for the specific query
query: The search query for which the data is recorded
search_type: The type of search result for the specific query
site_url: The URL of the site for which the search analytics data is captured

Returns: SearchAnalyticsByQuerySearchResult 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.

list(self, start_date: str, end_date: str, site_url: str, dimensions: list[str] | None = None, row_limit: int | None = None, start_row: int | None = None, type: str | None = None, aggregation_type: str | None = None, data_state: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.google_search_console.models.GoogleSearchConsoleExecuteResultWithMeta[list[SearchAnalyticsRow], SearchAnalyticsByQueryListResultMeta] : Query search analytics data grouped by date and query. Returns clicks, impressions, CTR, and average position for each search query.

aggregation_type: How data is aggregated: auto, byPage, byProperty.

data_state: Data freshness: final (stable data only) or all (includes fresh data).

site_url: The URL of the property as defined in Search Console. **kwargs: Additional parameters

Returns: SearchAnalyticsByQueryListResult

SitemapsQuery(connector: GoogleSearchConsoleConnector) : Query class for Sitemaps entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: SitemapsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.google_search_console.models.AirbyteSearchResult[SitemapsSearchData] : Search sitemaps records from Airbyte cache.

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

Available filter fields (SitemapsSearchFilter):

contents: Data related to the sitemap contents
errors: Errors encountered while processing the sitemaps
is_pending: Flag indicating if the sitemap is pending for processing
is_sitemaps_index: Flag indicating if the data represents a sitemap index
last_downloaded: Timestamp when the sitemap was last downloaded
last_submitted: Timestamp when the sitemap was last submitted
path: Path to the sitemap file
type_: Type of the sitemap
warnings: Warnings encountered while processing the sitemaps

Returns: SitemapsSearchResult 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, site_url: str, feedpath: str, **kwargs) ‑> airbyte_agent_sdk.connectors.google_search_console.models.Sitemap : Retrieves information about a specific sitemap.

Args: site_url: The URL of the property as defined in Search Console.

feedpath: The URL of the sitemap. **kwargs: Additional parameters

Returns: Sitemap

list(self, site_url: str, **kwargs) ‑> airbyte_agent_sdk.connectors.google_search_console.models.GoogleSearchConsoleExecuteResult[list[Sitemap]] : Lists the sitemaps submitted for a site.

Args: site_url: The URL of the property as defined in Search Console.

**kwargs: Additional parameters

Returns: SitemapsListResult

SitesQuery(connector: GoogleSearchConsoleConnector) : Query class for Sites entity operations.

Initialize query with connector reference.

Methods

context_store_search(self, query: SitesSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.google_search_console.models.AirbyteSearchResult[SitesSearchData] : Search sites records from Airbyte cache.

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

Available filter fields (SitesSearchFilter):

permission_level: The user's permission level for the site (owner, full, restricted, etc.)
site_url: The URL of the site data being fetched

Returns: SitesSearchResult 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, site_url: str, **kwargs) ‑> airbyte_agent_sdk.connectors.google_search_console.models.Site : Retrieves information about a specific site.

Args: site_url: The URL of the property as defined in Search Console. Examples: http://www.example.com/ (for a URL-prefix property) or sc-domain:example.com (for a Domain property)

**kwargs: Additional parameters

Returns: Site

list(self, **kwargs) ‑> airbyte_agent_sdk.connectors.google_search_console.models.GoogleSearchConsoleExecuteResult[list[Site]] : Lists the user's Search Console sites.

Returns: SitesListResult

Classes​

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​

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Classes

Class variables

Static methods

Legacy: one generated-description tool

Instance variables

Methods

Methods

Methods

Methods

Methods

Methods

Methods

Methods

Methods