Module airbyte_agent_sdk.connectors.sentry

Sentry connector for Airbyte SDK.

Auto-generated from OpenAPI specification.

Sub-modules

• airbyte_agent_sdk.connectors.sentry.connector
• airbyte_agent_sdk.connectors.sentry.connector_model
• airbyte_agent_sdk.connectors.sentry.models
• airbyte_agent_sdk.connectors.sentry.types

Classes

AirbyteAuthConfig(**data: Any) : Authentication configuration for Airbyte hosted mode execution.

Pass this to the connector's auth_config parameter to use hosted mode, where API credentials are stored securely in Airbyte Cloud.

For hosted mode execution, provide client credentials with either:

• connector_id: Direct connector/source ID (skips lookup)
• workspace_name: Workspace name for connector lookup

Attributes: workspace_name: Workspace name for hosted mode connector lookup organization_id: Optional Airbyte organization ID for multi-org selection airbyte_client_id: Airbyte OAuth client ID (required for hosted mode) airbyte_client_secret: Airbyte OAuth client secret (required for hosted mode) connector_id: Specific connector/source ID (skips lookup if provided)

Examples:

Hosted mode with connector_id (no lookup needed)

connector = GongConnector( auth_config=AirbyteAuthConfig( airbyte_client_id="client_abc123", airbyte_client_secret="secret_xyz789", connector_id="existing-source-uuid" ) )

Hosted mode with workspace_name (lookup by workspace)

connector = GongConnector( auth_config=AirbyteAuthConfig( workspace_name="user-123", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc123", airbyte_client_secret="secret_xyz789" ) )

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel

Class variables

airbyte_client_id: str | None : The type of the None singleton.

airbyte_client_secret: str | None : The type of the None singleton.

connector_id: str | None : The type of the None singleton.

model_config : The type of the None singleton.

organization_id: str | None : The type of the None singleton.

workspace_name: str | None : The type of the None singleton.

AirbyteSearchMeta(**data: Any) : Pagination metadata for search responses.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel

Class variables

cursor: str | None : Cursor for fetching the next page of results.

has_more: bool : Whether more results are available.

model_config : The type of the None singleton.

took_ms: int | None : Time taken to execute the search in milliseconds.

AirbyteSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel
• typing.Generic

Descendants

• airbyte_agent_sdk.connectors.sentry.models.AirbyteSearchResult[EventsSearchData]
• airbyte_agent_sdk.connectors.sentry.models.AirbyteSearchResult[IssuesSearchData]
• airbyte_agent_sdk.connectors.sentry.models.AirbyteSearchResult[ProjectsSearchData]
• airbyte_agent_sdk.connectors.sentry.models.AirbyteSearchResult[ReleasesSearchData]

Class variables

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

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

model_config : The type of the None singleton.

EventsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• airbyte_agent_sdk.connectors.sentry.models.AirbyteSearchResult
• pydantic.main.BaseModel
• typing.Generic

IssuesSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• airbyte_agent_sdk.connectors.sentry.models.AirbyteSearchResult
• pydantic.main.BaseModel
• typing.Generic

ProjectsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• airbyte_agent_sdk.connectors.sentry.models.AirbyteSearchResult
• pydantic.main.BaseModel
• typing.Generic

ReleasesSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• airbyte_agent_sdk.connectors.sentry.models.AirbyteSearchResult
• pydantic.main.BaseModel
• typing.Generic

EventsSearchData(**data: Any) : Search result data for events entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel

Class variables

context: dict[str, typing.Any] | None : Additional context data.

contexts: dict[str, typing.Any] | None : Structured context information.

crash_file: str | None : Crash file reference.

culprit: str | None : The culprit (source) of the event.

date_created: str | None : When the event was created.

date_received: str | None : When the event was received by Sentry.

dist: str | None : Distribution information.

entries: list[typing.Any] | None : Event entries (exception, breadcrumbs, request, etc.).

errors: list[typing.Any] | None : Processing errors.

event_id: str | None : Event ID as reported by the client.

event_type: str | None : The type of the event.

fingerprints: list[typing.Any] | None : Fingerprints used for grouping.

group_id: str | None : ID of the issue group this event belongs to.

grouping_config: dict[str, typing.Any] | None : Grouping configuration.

id: str | None : Unique event identifier.

location: str | None : Location in source code.

message: str | None : Event message.

meta: dict[str, typing.Any] | None : Meta information for data scrubbing.

metadata: dict[str, typing.Any] | None : Event metadata.

model_config : The type of the None singleton.

occurrence: str | None : Occurrence information for the event.

packages: dict[str, typing.Any] | None : Package information.

platform: str | None : Platform the event was generated on.

project_id: str | None : Project ID this event belongs to.

sdk: str | None : SDK information.

size: int | None : Event payload size in bytes.

tags: list[typing.Any] | None : Tags associated with the event.

title: str | None : Event title.

type_: str | None : Event type.

user: dict[str, typing.Any] | None : User associated with the event.

IssuesSearchData(**data: Any) : Search result data for issues entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel

Class variables

annotations: list[typing.Any] | None : Annotations on the issue.

assigned_to: dict[str, typing.Any] | None : User or team assigned to this issue.

count: str | None : Number of events for this issue.

culprit: str | None : The culprit (source) of the issue.

first_seen: str | None : When the issue was first seen.

has_seen: bool | None : Whether the authenticated user has seen the issue.

id: str | None : Unique issue identifier.

is_bookmarked: bool | None : Whether the issue is bookmarked.

is_public: bool | None : Whether the issue is public.

is_subscribed: bool | None : Whether the user is subscribed to the issue.

is_unhandled: bool | None : Whether the issue is from an unhandled error.

issue_category: str | None : The category classification of the issue.

issue_type: str | None : The type classification of the issue.

last_seen: str | None : When the issue was last seen.

level: str | None : Issue severity level.

logger: str | None : Logger that generated the issue.

metadata: dict[str, typing.Any] | None : Issue metadata.

model_config : The type of the None singleton.

num_comments: int | None : Number of comments on the issue.

permalink: str | None : Permalink to the issue in the Sentry UI.

platform: str | None : Platform for this issue.

project: dict[str, typing.Any] | None : Project this issue belongs to.

share_id: str | None : Share ID if the issue is shared.

short_id: str | None : Short human-readable identifier.

stats: dict[str, typing.Any] | None : Issue event statistics.

status: str | None : Issue status (resolved, unresolved, ignored).

status_details: dict[str, typing.Any] | None : Status detail information.

subscription_details: dict[str, typing.Any] | None : Subscription details.

substatus: str | None : Issue substatus.

title: str | None : Issue title.

type_: str | None : Issue type.

user_count: int | None : Number of users affected.

ProjectsSearchData(**data: Any) : Search result data for projects entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel

Class variables

access: list[typing.Any] | None : List of access permissions for the authenticated user.

avatar: dict[str, typing.Any] | None : Project avatar information.

color: str | None : Project color code.

date_created: str | None : Date the project was created.

features: list[typing.Any] | None : List of enabled features.

first_event: str | None : Timestamp of the first event.

first_transaction_event: bool | None : Whether a transaction event has been received.

has_access: bool | None : Whether the user has access to this project.

has_custom_metrics: bool | None : Whether the project has custom metrics.

has_feedbacks: bool | None : Whether the project has user feedback.

has_minified_stack_trace: bool | None : Whether the project has minified stack traces.

has_monitors: bool | None : Whether the project has cron monitors.

has_new_feedbacks: bool | None : Whether the project has new user feedback.

has_profiles: bool | None : Whether the project has profiling data.

has_replays: bool | None : Whether the project has session replays.

has_sessions: bool | None : Whether the project has session data.

id: str | None : Unique project identifier.

is_bookmarked: bool | None : Whether the project is bookmarked.

is_internal: bool | None : Whether the project is internal.

is_member: bool | None : Whether the authenticated user is a member.

is_public: bool | None : Whether the project is public.

model_config : The type of the None singleton.

name: str | None : Human-readable project name.

organization: dict[str, typing.Any] | None : Organization this project belongs to.

platform: str | None : The platform for this project.

slug: str | None : URL-friendly project identifier.

status: str | None : Project status.

ReleasesSearchData(**data: Any) : Search result data for releases entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel

Class variables

authors: list[typing.Any] | None : Authors of commits in this release.

commit_count: int | None : Number of commits in this release.

current_project_meta: dict[str, typing.Any] | None : Metadata for the current project context.

data: dict[str, typing.Any] | None : Additional release data.

date_created: str | None : When the release was created.

date_released: str | None : When the release was deployed.

deploy_count: int | None : Number of deploys for this release.

first_event: str | None : Timestamp of the first event in this release.

id: int | None : Unique release identifier.

last_commit: dict[str, typing.Any] | None : Last commit in this release.

last_deploy: dict[str, typing.Any] | None : Last deploy of this release.

last_event: str | None : Timestamp of the last event in this release.

model_config : The type of the None singleton.

new_groups: int | None : Number of new issue groups in this release.

owner: str | None : Owner of the release.

projects: list[typing.Any] | None : Projects associated with this release.

ref: str | None : Git reference (commit SHA, tag, etc.).

short_version: str | None : Short version string.

status: str | None : Release status.

url: str | None : URL associated with the release.

user_agent: str | None : User agent that created the release.

version: str | None : Release version string.

version_info: dict[str, typing.Any] | None : Parsed version information.

SentryAuthConfig(**data: Any) : Authentication Token

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel

Class variables

auth_token: str : Sentry authentication token. Log into Sentry and create one at Settings > Account > API > Auth Tokens.

model_config : The type of the None singleton.

SentryConnector(auth_config: SentryAuthConfig | AirbyteAuthConfig | BaseModel | None = None, on_token_refresh: Any | None = None, hostname: str | None = None) : Type-safe Sentry API connector.

Auto-generated from OpenAPI specification with full type safety.

Initialize a new sentry connector instance.

Supports both local and hosted execution modes:

• Local mode: Provide connector-specific auth config (e.g., SentryAuthConfig)
• 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) hostname: Host name of Sentry API server. For self-hosted instances, specify your host name here. Otherwise, leave as sentry.io. Examples:

Local mode (direct API calls)

connector = SentryConnector(auth_config=SentryAuthConfig(auth_token="..."))

Hosted mode with explicit connector_id (no lookup needed)

connector = SentryConnector( 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 = SentryConnector( 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: "'SentryAuthConfig'", name: str | None = None, replication_config: "'SentryReplicationConfig' | None" = None, source_template_id: str | None = None) : Create a new hosted connector on Airbyte Cloud.

This factory method:

1. Creates a source on Airbyte Cloud with the provided credentials
2. 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: Typed replication settings. 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 SentryConnector instance configured in hosted mode

Example:

Create a new hosted connector with API key auth

connector = await SentryConnector.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=SentryAuthConfig(auth_token="..."), )

With replication config (required for this connector):

connector = await SentryConnector.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=SentryAuthConfig(auth_token="..."), replication_config=SentryReplicationConfig(organization="...", project="..."), )

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

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

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

Methods

check(self) ‑> airbyte_agent_sdk.connectors.sentry.models.SentryCheckResult : 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: SentryCheckResult with status ("healthy" or "unhealthy") and optional error message

Example: result = await connector.check() if result.status == "healthy": print("Connection verified!") else: print(f"Check failed: {result.error}")

close(self) : Close the connector and release resources.

entity_schema(self, entity: str) ‑> dict[str, typing.Any] | None : Get the JSON schema for an entity.

Args: entity: Entity name (e.g., "contacts", "companies")

Returns: JSON schema dict describing the entity structure, or None if not found.

Example: schema = connector.entity_schema("contacts") if schema: print(f"Contact properties: {list(schema.get('properties', {}).keys())}")

execute(self, entity: str, action: "Literal['list', 'get', 'context_store_search']", params: Mapping[str, Any] | None = None) ‑> Any : Execute an entity operation with full type safety.

This is the recommended interface for blessed connectors as it:

• Uses the same signature as non-blessed connectors
• Provides full IDE autocomplete for entity/action/params
• Makes migration from generic to blessed connectors seamless

Args: entity: Entity name (e.g., "customers") action: Operation action (e.g., "create", "get", "list") params: Operation parameters (typed based on entity+action)

Returns: Typed response based on the operation

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

list_entities(self) ‑> list[dict[str, typing.Any]] : Get structured data about available entities, actions, and parameters.

Returns a list of entity descriptions with:

• entity_name: Name of the entity (e.g., "contacts", "deals")
• description: Entity description from the first endpoint
• available_actions: List of actions (e.g., ["list", "get", "create"])
• parameters: Dict mapping action -> list of parameter dicts

Example: entities = connector.list_entities() for entity in entities: print(f"{entity['entity_name']}: {entity['available_actions']}")

SentryReplicationConfig(**data: Any) : Replication Configuration - Settings for data replication from Sentry.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

• pydantic.main.BaseModel

Class variables

model_config : The type of the None singleton.

organization: str : The slug of the organization to replicate data from.

project: str : The slug of the project to replicate data from.