vendor_fabric.cursor

Cursor Connector - HTTP client for Cursor Background Agent API.

This connector provides Python access to the Cursor Background Agent API for managing AI coding agents through shared extended-data connector patterns.

Usage: from vendor_fabric.cursor import CursorConnector

connector = CursorConnector(api_key="...")
agents = connector.list_agents()

agent = connector.launch_agent(
    prompt_text="Implement feature X",
    repository="org/repo",
    ref="main"
)

Reference: https://cursor.com/docs/cloud-agent/api/endpoints

Submodules

• vendor_fabric.cursor.tools

Package Contents

Classes

AgentState	Agent execution state.
Agent	Cursor Background Agent representation.
Repository	Repository available for Cursor agents.
ConversationMessage	Single message in agent conversation.
Conversation	Agent conversation history.
LaunchOptions	Options for launching a new agent.
CursorConnector	Cursor Background Agent API connector.

Functions

validate_agent_id	Validate an agent ID to prevent injection attacks.
validate_prompt_text	Validate prompt text.
validate_repository	Validate repository name.
validate_webhook_url	Validate webhook URL to prevent SSRF attacks.
sanitize_error	Sanitize error messages to prevent sensitive data leakage.

Data

DEFAULT_BASE_URL
DEFAULT_TIMEOUT
MAX_PROMPT_LENGTH
MAX_REPO_LENGTH
AGENT_ID_PATTERN
BLOCKED_HOSTNAME_PATTERNS

API

vendor_fabric.cursor.DEFAULT_BASE_URL = 'https://api.cursor.com/v0'

vendor_fabric.cursor.DEFAULT_TIMEOUT = 60.0

vendor_fabric.cursor.MAX_PROMPT_LENGTH = 100000

vendor_fabric.cursor.MAX_REPO_LENGTH = 200

vendor_fabric.cursor.AGENT_ID_PATTERN = 'compile(...)'

vendor_fabric.cursor.BLOCKED_HOSTNAME_PATTERNS = None

exception vendor_fabric.cursor.CursorError(message: str, status_code: int | None = None)

Bases: Exception

Base exception for Cursor API errors.

Initialization

Initialize self. See help(type(self)) for accurate signature.

add_note()

class args

with_traceback()

exception vendor_fabric.cursor.CursorValidationError(message: str, status_code: int | None = None)

Bases: vendor_fabric.cursor.CursorError

Validation error for Cursor API inputs.

Initialization

Initialize self. See help(type(self)) for accurate signature.

add_note()

class args

with_traceback()

exception vendor_fabric.cursor.CursorAPIError(message: str, status_code: int | None = None)

Bases: vendor_fabric.cursor.CursorError

API error from Cursor service.

Initialization

Initialize self. See help(type(self)) for accurate signature.

add_note()

class args

with_traceback()

class vendor_fabric.cursor.AgentState

Bases: enum.StrEnum

Agent execution state.

Initialization

Initialize self. See help(type(self)) for accurate signature.

PENDING = 'pending'

RUNNING = 'running'

FINISHED = 'finished'

ERRORED = 'errored'

CANCELLED = 'cancelled'

capitalize()

casefold()

center()

count()

encode()

endswith()

expandtabs()

find()

format()

format_map()

index()

isalnum()

isalpha()

isascii()

isdecimal()

isdigit()

isidentifier()

islower()

isnumeric()

isprintable()

isspace()

istitle()

isupper()

join()

ljust()

lower()

lstrip()

partition()

removeprefix()

removesuffix()

replace()

rfind()

rindex()

rjust()

rpartition()

rsplit()

rstrip()

split()

splitlines()

startswith()

strip()

swapcase()

title()

translate()

upper()

zfill()

name()

value()

class vendor_fabric.cursor.Agent(/, **data: Any)

Bases: pydantic.BaseModel

Cursor Background Agent representation.

Initialization

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.

model_config = 'ConfigDict(...)'

id: str = 'Field(...)'

state: vendor_fabric.cursor.AgentState = 'Field(...)'

task: str | None = 'Field(...)'

repository: str | None = 'Field(...)'

branch: str | None = 'Field(...)'

pr_number: int | None = 'Field(...)'

pr_url: str | None = 'Field(...)'

created_at: datetime.datetime | None = 'Field(...)'

updated_at: datetime.datetime | None = 'Field(...)'

model: str | None = 'Field(...)'

error: str | None = 'Field(...)'

classmethod model_fields() → dict[str, pydantic.fields.FieldInfo]

classmethod model_computed_fields() → dict[str, pydantic.fields.ComputedFieldInfo]

property model_extra: dict[str, Any] | None

property model_fields_set: set[str]

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → typing_extensions.Self

model_copy(*, update: collections.abc.Mapping[str, Any] | None = None, deep: bool = False) → typing_extensions.Self

model_dump(*, mode: Literal[json, python] | str = 'python', include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, context: Any | None = None, by_alias: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, exclude_computed_fields: bool = False, round_trip: bool = False, warnings: bool | Literal[none, warn, error] = True, fallback: Callable[[Any], Any] | None = None, serialize_as_any: bool = False, polymorphic_serialization: bool | None = None) → dict[str, Any]

model_dump_json(*, indent: int | None = None, ensure_ascii: bool = False, include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, context: Any | None = None, by_alias: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, exclude_computed_fields: bool = False, round_trip: bool = False, warnings: bool | Literal[none, warn, error] = True, fallback: Callable[[Any], Any] | None = None, serialize_as_any: bool = False, polymorphic_serialization: bool | None = None) → str

classmethod model_json_schema(by_alias: bool = True, ref_template: str = DEFAULT_REF_TEMPLATE, schema_generator: type[pydantic.json_schema.GenerateJsonSchema] = GenerateJsonSchema, mode: pydantic.json_schema.JsonSchemaMode = 'validation', *, union_format: Literal[any_of, primitive_type_array] = 'any_of') → dict[str, Any]

classmethod model_parametrized_name(params: tuple[type[Any], ...]) → str

model_post_init(context: Any, /) → None

classmethod model_rebuild(*, force: bool = False, raise_errors: bool = True, _parent_namespace_depth: int = 2, _types_namespace: pydantic._internal._namespace_utils.MappingNamespace | None = None) → bool | None

classmethod model_validate(obj: Any, *, strict: bool | None = None, extra: pydantic.config.ExtraValues | None = None, from_attributes: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → typing_extensions.Self

classmethod model_validate_json(json_data: str | bytes | bytearray, *, strict: bool | None = None, extra: pydantic.config.ExtraValues | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → typing_extensions.Self

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, extra: pydantic.config.ExtraValues | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → typing_extensions.Self

dict(*, include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → Dict[str, Any]

json(*, include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Callable[[Any], Any] | None = PydanticUndefined, models_as_dict: bool = PydanticUndefined, **dumps_kwargs: Any) → str

classmethod parse_obj(obj: Any) → typing_extensions.Self

classmethod parse_raw(b: str | bytes, *, content_type: str | None = None, encoding: str = 'utf8', proto: pydantic.deprecated.parse.Protocol | None = None, allow_pickle: bool = False) → typing_extensions.Self

classmethod parse_file(path: str | pathlib.Path, *, content_type: str | None = None, encoding: str = 'utf8', proto: pydantic.deprecated.parse.Protocol | None = None, allow_pickle: bool = False) → typing_extensions.Self

classmethod from_orm(obj: Any) → typing_extensions.Self

classmethod construct(_fields_set: set[str] | None = None, **values: Any) → typing_extensions.Self

copy(*, include: pydantic._internal._utils.AbstractSetIntStr | pydantic._internal._utils.MappingIntStrAny | None = None, exclude: pydantic._internal._utils.AbstractSetIntStr | pydantic._internal._utils.MappingIntStrAny | None = None, update: Dict[str, Any] | None = None, deep: bool = False) → typing_extensions.Self

classmethod schema(by_alias: bool = True, ref_template: str = DEFAULT_REF_TEMPLATE) → Dict[str, Any]

classmethod schema_json(*, by_alias: bool = True, ref_template: str = DEFAULT_REF_TEMPLATE, **dumps_kwargs: Any) → str

classmethod validate(value: Any) → typing_extensions.Self

classmethod update_forward_refs(**localns: Any) → None

class vendor_fabric.cursor.Repository(/, **data: Any)

Bases: pydantic.BaseModel

Repository available for Cursor agents.

Initialization

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.

model_config = 'ConfigDict(...)'

name: str = 'Field(...)'

url: str | None = 'Field(...)'

default_branch: str | None = 'Field(...)'

private: bool | None = 'Field(...)'

classmethod model_fields() → dict[str, pydantic.fields.FieldInfo]

classmethod model_computed_fields() → dict[str, pydantic.fields.ComputedFieldInfo]

property model_extra: dict[str, Any] | None

property model_fields_set: set[str]

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → typing_extensions.Self

model_copy(*, update: collections.abc.Mapping[str, Any] | None = None, deep: bool = False) → typing_extensions.Self

model_dump(*, mode: Literal[json, python] | str = 'python', include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, context: Any | None = None, by_alias: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, exclude_computed_fields: bool = False, round_trip: bool = False, warnings: bool | Literal[none, warn, error] = True, fallback: Callable[[Any], Any] | None = None, serialize_as_any: bool = False, polymorphic_serialization: bool | None = None) → dict[str, Any]

model_dump_json(*, indent: int | None = None, ensure_ascii: bool = False, include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, context: Any | None = None, by_alias: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, exclude_computed_fields: bool = False, round_trip: bool = False, warnings: bool | Literal[none, warn, error] = True, fallback: Callable[[Any], Any] | None = None, serialize_as_any: bool = False, polymorphic_serialization: bool | None = None) → str

classmethod model_json_schema(by_alias: bool = True, ref_template: str = DEFAULT_REF_TEMPLATE, schema_generator: type[pydantic.json_schema.GenerateJsonSchema] = GenerateJsonSchema, mode: pydantic.json_schema.JsonSchemaMode = 'validation', *, union_format: Literal[any_of, primitive_type_array] = 'any_of') → dict[str, Any]

classmethod model_parametrized_name(params: tuple[type[Any], ...]) → str

model_post_init(context: Any, /) → None

classmethod model_rebuild(*, force: bool = False, raise_errors: bool = True, _parent_namespace_depth: int = 2, _types_namespace: pydantic._internal._namespace_utils.MappingNamespace | None = None) → bool | None

classmethod model_validate(obj: Any, *, strict: bool | None = None, extra: pydantic.config.ExtraValues | None = None, from_attributes: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → typing_extensions.Self

classmethod model_validate_json(json_data: str | bytes | bytearray, *, strict: bool | None = None, extra: pydantic.config.ExtraValues | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → typing_extensions.Self

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, extra: pydantic.config.ExtraValues | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → typing_extensions.Self

dict(*, include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → Dict[str, Any]

json(*, include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Callable[[Any], Any] | None = PydanticUndefined, models_as_dict: bool = PydanticUndefined, **dumps_kwargs: Any) → str

classmethod parse_obj(obj: Any) → typing_extensions.Self

classmethod parse_raw(b: str | bytes, *, content_type: str | None = None, encoding: str = 'utf8', proto: pydantic.deprecated.parse.Protocol | None = None, allow_pickle: bool = False) → typing_extensions.Self

classmethod parse_file(path: str | pathlib.Path, *, content_type: str | None = None, encoding: str = 'utf8', proto: pydantic.deprecated.parse.Protocol | None = None, allow_pickle: bool = False) → typing_extensions.Self

classmethod from_orm(obj: Any) → typing_extensions.Self

classmethod construct(_fields_set: set[str] | None = None, **values: Any) → typing_extensions.Self

copy(*, include: pydantic._internal._utils.AbstractSetIntStr | pydantic._internal._utils.MappingIntStrAny | None = None, exclude: pydantic._internal._utils.AbstractSetIntStr | pydantic._internal._utils.MappingIntStrAny | None = None, update: Dict[str, Any] | None = None, deep: bool = False) → typing_extensions.Self

classmethod schema(by_alias: bool = True, ref_template: str = DEFAULT_REF_TEMPLATE) → Dict[str, Any]

classmethod schema_json(*, by_alias: bool = True, ref_template: str = DEFAULT_REF_TEMPLATE, **dumps_kwargs: Any) → str

classmethod validate(value: Any) → typing_extensions.Self

classmethod update_forward_refs(**localns: Any) → None

class vendor_fabric.cursor.ConversationMessage(/, **data: Any)

Bases: pydantic.BaseModel

Single message in agent conversation.

Initialization

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.

model_config = 'ConfigDict(...)'

role: str = 'Field(...)'

content: str = 'Field(...)'

timestamp: datetime.datetime | None = 'Field(...)'

classmethod model_fields() → dict[str, pydantic.fields.FieldInfo]

classmethod model_computed_fields() → dict[str, pydantic.fields.ComputedFieldInfo]

property model_extra: dict[str, Any] | None

property model_fields_set: set[str]

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → typing_extensions.Self

model_copy(*, update: collections.abc.Mapping[str, Any] | None = None, deep: bool = False) → typing_extensions.Self

model_dump(*, mode: Literal[json, python] | str = 'python', include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, context: Any | None = None, by_alias: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, exclude_computed_fields: bool = False, round_trip: bool = False, warnings: bool | Literal[none, warn, error] = True, fallback: Callable[[Any], Any] | None = None, serialize_as_any: bool = False, polymorphic_serialization: bool | None = None) → dict[str, Any]

model_dump_json(*, indent: int | None = None, ensure_ascii: bool = False, include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, context: Any | None = None, by_alias: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, exclude_computed_fields: bool = False, round_trip: bool = False, warnings: bool | Literal[none, warn, error] = True, fallback: Callable[[Any], Any] | None = None, serialize_as_any: bool = False, polymorphic_serialization: bool | None = None) → str

classmethod model_json_schema(by_alias: bool = True, ref_template: str = DEFAULT_REF_TEMPLATE, schema_generator: type[pydantic.json_schema.GenerateJsonSchema] = GenerateJsonSchema, mode: pydantic.json_schema.JsonSchemaMode = 'validation', *, union_format: Literal[any_of, primitive_type_array] = 'any_of') → dict[str, Any]

classmethod model_parametrized_name(params: tuple[type[Any], ...]) → str

model_post_init(context: Any, /) → None

classmethod model_rebuild(*, force: bool = False, raise_errors: bool = True, _parent_namespace_depth: int = 2, _types_namespace: pydantic._internal._namespace_utils.MappingNamespace | None = None) → bool | None

classmethod model_validate(obj: Any, *, strict: bool | None = None, extra: pydantic.config.ExtraValues | None = None, from_attributes: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → typing_extensions.Self

classmethod model_validate_json(json_data: str | bytes | bytearray, *, strict: bool | None = None, extra: pydantic.config.ExtraValues | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → typing_extensions.Self

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, extra: pydantic.config.ExtraValues | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → typing_extensions.Self

dict(*, include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → Dict[str, Any]

json(*, include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Callable[[Any], Any] | None = PydanticUndefined, models_as_dict: bool = PydanticUndefined, **dumps_kwargs: Any) → str

classmethod parse_obj(obj: Any) → typing_extensions.Self

classmethod parse_raw(b: str | bytes, *, content_type: str | None = None, encoding: str = 'utf8', proto: pydantic.deprecated.parse.Protocol | None = None, allow_pickle: bool = False) → typing_extensions.Self

classmethod parse_file(path: str | pathlib.Path, *, content_type: str | None = None, encoding: str = 'utf8', proto: pydantic.deprecated.parse.Protocol | None = None, allow_pickle: bool = False) → typing_extensions.Self

classmethod from_orm(obj: Any) → typing_extensions.Self

classmethod construct(_fields_set: set[str] | None = None, **values: Any) → typing_extensions.Self

copy(*, include: pydantic._internal._utils.AbstractSetIntStr | pydantic._internal._utils.MappingIntStrAny | None = None, exclude: pydantic._internal._utils.AbstractSetIntStr | pydantic._internal._utils.MappingIntStrAny | None = None, update: Dict[str, Any] | None = None, deep: bool = False) → typing_extensions.Self

classmethod schema(by_alias: bool = True, ref_template: str = DEFAULT_REF_TEMPLATE) → Dict[str, Any]

classmethod schema_json(*, by_alias: bool = True, ref_template: str = DEFAULT_REF_TEMPLATE, **dumps_kwargs: Any) → str

classmethod validate(value: Any) → typing_extensions.Self

classmethod update_forward_refs(**localns: Any) → None

class vendor_fabric.cursor.Conversation(/, **data: Any)

Bases: pydantic.BaseModel

Agent conversation history.

Initialization

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.

model_config = 'ConfigDict(...)'

agent_id: str = 'Field(...)'

messages: list[vendor_fabric.cursor.ConversationMessage] = 'Field(...)'

classmethod model_fields() → dict[str, pydantic.fields.FieldInfo]

classmethod model_computed_fields() → dict[str, pydantic.fields.ComputedFieldInfo]

property model_extra: dict[str, Any] | None

property model_fields_set: set[str]

classmethod model_construct(_fields_set: set[str] | None = None, **values: Any) → typing_extensions.Self

model_copy(*, update: collections.abc.Mapping[str, Any] | None = None, deep: bool = False) → typing_extensions.Self

model_dump(*, mode: Literal[json, python] | str = 'python', include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, context: Any | None = None, by_alias: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, exclude_computed_fields: bool = False, round_trip: bool = False, warnings: bool | Literal[none, warn, error] = True, fallback: Callable[[Any], Any] | None = None, serialize_as_any: bool = False, polymorphic_serialization: bool | None = None) → dict[str, Any]

model_dump_json(*, indent: int | None = None, ensure_ascii: bool = False, include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, context: Any | None = None, by_alias: bool | None = None, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, exclude_computed_fields: bool = False, round_trip: bool = False, warnings: bool | Literal[none, warn, error] = True, fallback: Callable[[Any], Any] | None = None, serialize_as_any: bool = False, polymorphic_serialization: bool | None = None) → str

classmethod model_json_schema(by_alias: bool = True, ref_template: str = DEFAULT_REF_TEMPLATE, schema_generator: type[pydantic.json_schema.GenerateJsonSchema] = GenerateJsonSchema, mode: pydantic.json_schema.JsonSchemaMode = 'validation', *, union_format: Literal[any_of, primitive_type_array] = 'any_of') → dict[str, Any]

classmethod model_parametrized_name(params: tuple[type[Any], ...]) → str

model_post_init(context: Any, /) → None

classmethod model_rebuild(*, force: bool = False, raise_errors: bool = True, _parent_namespace_depth: int = 2, _types_namespace: pydantic._internal._namespace_utils.MappingNamespace | None = None) → bool | None

classmethod model_validate(obj: Any, *, strict: bool | None = None, extra: pydantic.config.ExtraValues | None = None, from_attributes: bool | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → typing_extensions.Self

classmethod model_validate_json(json_data: str | bytes | bytearray, *, strict: bool | None = None, extra: pydantic.config.ExtraValues | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → typing_extensions.Self

classmethod model_validate_strings(obj: Any, *, strict: bool | None = None, extra: pydantic.config.ExtraValues | None = None, context: Any | None = None, by_alias: bool | None = None, by_name: bool | None = None) → typing_extensions.Self

dict(*, include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False) → Dict[str, Any]

json(*, include: pydantic.main.IncEx | None = None, exclude: pydantic.main.IncEx | None = None, by_alias: bool = False, exclude_unset: bool = False, exclude_defaults: bool = False, exclude_none: bool = False, encoder: Callable[[Any], Any] | None = PydanticUndefined, models_as_dict: bool = PydanticUndefined, **dumps_kwargs: Any) → str

classmethod parse_obj(obj: Any) → typing_extensions.Self

classmethod parse_raw(b: str | bytes, *, content_type: str | None = None, encoding: str = 'utf8', proto: pydantic.deprecated.parse.Protocol | None = None, allow_pickle: bool = False) → typing_extensions.Self

classmethod parse_file(path: str | pathlib.Path, *, content_type: str | None = None, encoding: str = 'utf8', proto: pydantic.deprecated.parse.Protocol | None = None, allow_pickle: bool = False) → typing_extensions.Self

classmethod from_orm(obj: Any) → typing_extensions.Self

classmethod construct(_fields_set: set[str] | None = None, **values: Any) → typing_extensions.Self

copy(*, include: pydantic._internal._utils.AbstractSetIntStr | pydantic._internal._utils.MappingIntStrAny | None = None, exclude: pydantic._internal._utils.AbstractSetIntStr | pydantic._internal._utils.MappingIntStrAny | None = None, update: Dict[str, Any] | None = None, deep: bool = False) → typing_extensions.Self

classmethod schema(by_alias: bool = True, ref_template: str = DEFAULT_REF_TEMPLATE) → Dict[str, Any]

classmethod schema_json(*, by_alias: bool = True, ref_template: str = DEFAULT_REF_TEMPLATE, **dumps_kwargs: Any) → str

classmethod validate(value: Any) → typing_extensions.Self

classmethod update_forward_refs(**localns: Any) → None

class vendor_fabric.cursor.LaunchOptions

Options for launching a new agent.

prompt_text: str = None

repository: str = None

ref: str | None = None

images: list[dict[str, Any]] | None = None

auto_create_pr: bool = True

branch_name: str | None = None

open_as_cursor_github_app: bool = True

skip_reviewer_request: bool = False

webhook_url: str | None = None

webhook_secret: str | None = None

vendor_fabric.cursor.validate_agent_id(agent_id: str) → None

Validate an agent ID to prevent injection attacks.

Args: agent_id: The agent ID to validate.

Raises: CursorValidationError: If the agent ID is invalid.

vendor_fabric.cursor.validate_prompt_text(text: str) → None

Validate prompt text.

Args: text: The prompt text to validate.

Raises: CursorValidationError: If the prompt is invalid.

vendor_fabric.cursor.validate_repository(repository: str) → None

Validate repository name.

Args: repository: The repository name to validate.

Raises: CursorValidationError: If the repository is invalid.

vendor_fabric.cursor.validate_webhook_url(url: str) → None

Validate webhook URL to prevent SSRF attacks.

Only allows HTTPS URLs to external hosts.

Args: url: The webhook URL to validate.

Raises: CursorValidationError: If the URL is invalid or potentially dangerous.

vendor_fabric.cursor.sanitize_error(error: Any, *, values: collections.abc.Iterable[Any] | None = None) → str

Sanitize error messages to prevent sensitive data leakage.

Args: error: The error to sanitize. values: Explicit caller-provided values that must not appear in diagnostics.

Returns: Sanitized error message string.

class vendor_fabric.cursor.CursorConnector(api_key: str | None = None, base_url: str | None = None, timeout: float = DEFAULT_TIMEOUT, logger: extended_data.logging.Logging | None = None, **kwargs: Any)

Bases: vendor_fabric.base.ConnectorBase

Cursor Background Agent API connector.

Provides HTTP client access to Cursor’s agent management API for spawning, monitoring, and coordinating AI coding agents.

Args: api_key: Cursor API key. Defaults to CURSOR_API_KEY env var. base_url: API base URL. Only override for testing. timeout: Request timeout in seconds. Default 60s. logger: Optional logger instance. **kwargs: Additional InputProvider arguments.

Example: >>> connector = CursorConnector() >>> agents = connector.list_agents() >>> for agent in agents: … print(f”{agent.id}: {agent.state}”)

Initialization

Initialize the connector.

Args: api_key: API key (overrides environment variable) base_url: Base URL (overrides class default) timeout: HTTP timeout in seconds logger: Logger instance **kwargs: Passed to InputProvider

API_KEY_ENV = 'CURSOR_API_KEY'

BASE_URL = None

static is_available() → bool

Check if API key is available.

Returns: True if CURSOR_API_KEY is set in environment.

list_agents() → extended_data.containers.ExtendedList[extended_data.containers.ExtendedDict]

List all agents.

Returns: List of agent payload dictionaries.

Raises: CursorAPIError: If the API request fails.

get_agent_status(agent_id: str) → extended_data.containers.ExtendedDict

Get status of a specific agent.

Args: agent_id: The agent identifier.

Returns: Agent payload dictionary with current status.

Raises: CursorValidationError: If agent_id is invalid. CursorAPIError: If the API request fails or returns empty response.

get_agent_conversation(agent_id: str) → extended_data.containers.ExtendedDict

Get conversation history for an agent.

Args: agent_id: The agent identifier.

Returns: Conversation payload dictionary with message history.

Raises: CursorValidationError: If agent_id is invalid. CursorAPIError: If the API request fails.

launch_agent(prompt_text: str, repository: str, ref: str | None = None, images: list[dict[str, Any]] | None = None, auto_create_pr: bool = True, branch_name: str | None = None, open_as_cursor_github_app: bool = True, skip_reviewer_request: bool = False, webhook_url: str | None = None, webhook_secret: str | None = None) → extended_data.containers.ExtendedDict

Launch a new agent.

Args: prompt_text: The task description for the agent. repository: Repository name (owner/repo) or URL. ref: Git ref (branch/tag/commit). Defaults to default branch. images: Optional list of images with data and dimensions. auto_create_pr: Whether to automatically create a PR. branch_name: Custom branch name for the PR. open_as_cursor_github_app: Open PR as Cursor GitHub App. skip_reviewer_request: Skip reviewer request on PR. webhook_url: Webhook URL for status updates. webhook_secret: Webhook secret for signature verification.

Returns: The launched agent payload dictionary.

Raises: CursorValidationError: If inputs are invalid. CursorAPIError: If the API request fails.

add_followup(agent_id: str, prompt_text: str) → None

Send a follow-up message to an agent.

Args: agent_id: The agent identifier. prompt_text: The follow-up message text.

Raises: CursorValidationError: If inputs are invalid. CursorAPIError: If the API request fails.

list_repositories() → extended_data.containers.ExtendedList[extended_data.containers.ExtendedDict]

List available repositories.

Returns: List of repository payload dictionaries.

Raises: CursorAPIError: If the API request fails.

list_models() → extended_data.containers.ExtendedList[extended_data.containers.ExtendedString]

List available models.

Returns: List of model names.

Raises: CursorAPIError: If the API request fails.

CONNECTOR_CATEGORY: ClassVar[str] = 'external'

CONNECTOR_CAPABILITIES: ClassVar[tuple[str, ...]] = ()

TIMEOUT: ClassVar[float] = 300.0

MIN_REQUEST_INTERVAL: ClassVar[float] = 0.0

MAX_RETRIES: ClassVar[int] = 5

property api_key: str

property client: httpx.Client

close() → None

request(method: str, endpoint: str, *, headers: dict[str, str] | None = None, **kwargs: Any) → httpx.Response

decode_response(response: httpx.Response, *, suffix: str | None = None, as_extended: bool = True) → Any

decode_response_file(response: httpx.Response, *, source: str | None = None, suffix: str | None = None, as_extended: bool = True, metadata: collections.abc.Mapping[str, Any] | None = None) → extended_data.io.DataFile

extend_result(value: Any) → Any

request_data(method: str, endpoint: str, *, headers: dict[str, str] | None = None, suffix: str | None = None, as_extended: bool = True, **kwargs: Any) → Any

request_data_file(method: str, endpoint: str, *, headers: dict[str, str] | None = None, suffix: str | None = None, as_extended: bool = True, **kwargs: Any) → extended_data.io.DataFile

request_workflow(method: str, endpoint: str, *, headers: dict[str, str] | None = None, suffix: str | None = None, as_extended: bool = True, **kwargs: Any) → extended_data.workflows.DataWorkflow

get(endpoint: str, **kwargs: Any) → httpx.Response

get_data(endpoint: str, *, suffix: str | None = None, as_extended: bool = True, **kwargs: Any) → Any

get_workflow(endpoint: str, *, suffix: str | None = None, as_extended: bool = True, **kwargs: Any) → extended_data.workflows.DataWorkflow

post(endpoint: str, **kwargs: Any) → httpx.Response

post_data(endpoint: str, *, suffix: str | None = None, as_extended: bool = True, **kwargs: Any) → Any

post_workflow(endpoint: str, *, suffix: str | None = None, as_extended: bool = True, **kwargs: Any) → extended_data.workflows.DataWorkflow

put(endpoint: str, **kwargs: Any) → httpx.Response

put_data(endpoint: str, *, suffix: str | None = None, as_extended: bool = True, **kwargs: Any) → Any

put_workflow(endpoint: str, *, suffix: str | None = None, as_extended: bool = True, **kwargs: Any) → extended_data.workflows.DataWorkflow

delete(endpoint: str, **kwargs: Any) → httpx.Response

delete_data(endpoint: str, *, suffix: str | None = None, as_extended: bool = True, **kwargs: Any) → Any

delete_workflow(endpoint: str, *, suffix: str | None = None, as_extended: bool = True, **kwargs: Any) → extended_data.workflows.DataWorkflow

patch(endpoint: str, **kwargs: Any) → httpx.Response

patch_data(endpoint: str, *, suffix: str | None = None, as_extended: bool = True, **kwargs: Any) → Any

patch_workflow(endpoint: str, *, suffix: str | None = None, as_extended: bool = True, **kwargs: Any) → extended_data.workflows.DataWorkflow

download(url: str, output_path: str) → int

vendor_capabilities: ClassVar[dict[str, vendor_fabric.capabilities.CapabilitySpec]] = None

vendor_capability_methods: ClassVar[dict[str, str]] = None

get_input(k: str, default: Any | None = None, required: bool = False, is_bool: bool = False, is_integer: bool = False, is_float: bool = False, is_path: bool = False, is_datetime: bool = False, as_extended: bool = False) → Any

decode_input(k: str, default: Any | None = None, required: bool = False, decode_from_json: bool = False, decode_from_yaml: bool = False, decode_from_base64: bool = False, allow_none: bool = True, as_extended: bool = False) → Any

freeze_inputs() → extended_data.containers.mappings.ExtendedDict

thaw_inputs() → extended_data.containers.mappings.ExtendedDict

snapshot_inputs(*, frozen: bool = False) → extended_data.containers.mappings.ExtendedDict

replace_inputs(new_inputs: collections.abc.Mapping[str, Any] | None, *, clear_frozen: bool = True) → extended_data.containers.mappings.ExtendedDict

merge_inputs(new_inputs: collections.abc.Mapping[str, Any] | None) → extended_data.containers.mappings.ExtendedDict

shift_inputs() → extended_data.containers.mappings.ExtendedDict