refactor: convert CrewBase decorator to metaclass pattern

src/crewai/project/crew_base.py

@@ -1,301 +1,447 @@
-"""Base decorator for creating crew classes with configuration and function management."""
+"""Base metaclass for creating crew classes with configuration and function management."""
+
+from __future__ import annotations
 
 import inspect
 import logging
 from collections.abc import Callable
 from pathlib import Path
-from typing import Any, TypeVar, cast
+from typing import TYPE_CHECKING, Any
 
 import yaml
 from dotenv import load_dotenv
 
 from crewai.tools import BaseTool
 
+if TYPE_CHECKING:
+    from crewai.crews.crew_output import CrewOutput
+    from crewai.project.wrappers import CrewInstance
+
 load_dotenv()
 
-T = TypeVar("T", bound=type)
 
+class CrewBaseMeta(type):
+    """Metaclass that adds crew functionality to classes."""
 
-def CrewBase(cls: T) -> T:  # noqa: N802
-    """Wraps a class with crew functionality and configuration management."""
+    def __new__(
+        mcs,
+        name: str,
+        bases: tuple[type, ...],
+        namespace: dict[str, Any],
+        **kwargs: Any,
+    ) -> type:
+        """Create crew class with configuration and method injection.
 
-    class WrappedClass(cls):  # type: ignore
-        is_crew_class: bool = True  # type: ignore
+        Args:
+            name: Class name.
+            bases: Base classes.
+            namespace: Class namespace dictionary.
+            **kwargs: Additional keyword arguments.
 
-        # Get the directory of the class being decorated
-        base_directory = Path(inspect.getfile(cls)).parent
+        Returns:
+            New crew class with injected methods and attributes.
+        """
+        cls = super().__new__(mcs, name, bases, namespace)
 
-        original_agents_config_path = getattr(
+        cls.is_crew_class = True  # type: ignore[attr-defined]
+        cls._crew_name = name  # type: ignore[attr-defined]
+
+        try:
+            cls.base_directory = Path(inspect.getfile(cls)).parent  # type: ignore[attr-defined]
+        except (TypeError, OSError):
+            cls.base_directory = Path.cwd()  # type: ignore[attr-defined]
+
+        cls.original_agents_config_path = getattr(  # type: ignore[attr-defined]
             cls, "agents_config", "config/agents.yaml"
         )
-        original_tasks_config_path = getattr(cls, "tasks_config", "config/tasks.yaml")
+        cls.original_tasks_config_path = getattr(  # type: ignore[attr-defined]
+            cls, "tasks_config", "config/tasks.yaml"
+        )
 
-        mcp_server_params: Any = getattr(cls, "mcp_server_params", None)
-        mcp_connect_timeout: int = getattr(cls, "mcp_connect_timeout", 30)
+        cls.mcp_server_params = getattr(cls, "mcp_server_params", None)  # type: ignore[attr-defined]
+        cls.mcp_connect_timeout = getattr(cls, "mcp_connect_timeout", 30)  # type: ignore[attr-defined]
 
-        def __init__(self, *args, **kwargs):
-            super().__init__(*args, **kwargs)
-            self.load_configurations()
-            self.map_all_agent_variables()
-            self.map_all_task_variables()
-            # Preserve all decorated functions
-            self._original_functions = {
-                name: method
-                for name, method in cls.__dict__.items()
-                if any(
-                    hasattr(method, attr)
-                    for attr in [
-                        "is_task",
-                        "is_agent",
-                        "is_before_kickoff",
-                        "is_after_kickoff",
-                        "is_kickoff",
-                    ]
-                )
-            }
-            # Store specific function types
-            self._original_tasks = self._filter_functions(
-                self._original_functions, "is_task"
-            )
-            self._original_agents = self._filter_functions(
-                self._original_functions, "is_agent"
-            )
-            self._before_kickoff = self._filter_functions(
-                self._original_functions, "is_before_kickoff"
-            )
-            self._after_kickoff = self._filter_functions(
-                self._original_functions, "is_after_kickoff"
-            )
-            self._kickoff = self._filter_functions(
-                self._original_functions, "is_kickoff"
-            )
+        cls._close_mcp_server = _close_mcp_server  # type: ignore[attr-defined]
+        cls.get_mcp_tools = get_mcp_tools  # type: ignore[attr-defined]
+        cls._load_config = _load_config  # type: ignore[attr-defined]
+        cls.load_configurations = load_configurations  # type: ignore[attr-defined]
+        cls.load_yaml = staticmethod(load_yaml)  # type: ignore[attr-defined]
+        cls.map_all_agent_variables = map_all_agent_variables  # type: ignore[attr-defined]
+        cls._map_agent_variables = _map_agent_variables  # type: ignore[attr-defined]
+        cls.map_all_task_variables = map_all_task_variables  # type: ignore[attr-defined]
+        cls._map_task_variables = _map_task_variables  # type: ignore[attr-defined]
 
-            # Add close mcp server method to after kickoff
-            bound_method = self._create_close_mcp_server_method()
-            self._after_kickoff["_close_mcp_server"] = bound_method
+        return cls
 
-        def _create_close_mcp_server_method(self):
-            def _close_mcp_server(self, instance, outputs):
-                adapter = getattr(self, "_mcp_server_adapter", None)
-                if adapter is not None:
-                    try:
-                        adapter.stop()
-                    except Exception as e:
-                        logging.warning(f"Error stopping MCP server: {e}")
-                return outputs
+    def __call__(cls, *args: Any, **kwargs: Any) -> CrewInstance:
+        """Intercept instance creation to initialize crew functionality.
 
-            _close_mcp_server.is_after_kickoff = True
+        Args:
+            *args: Positional arguments for instance creation.
+            **kwargs: Keyword arguments for instance creation.
 
-            import types
+        Returns:
+            Initialized crew instance.
+        """
+        instance: CrewInstance = super().__call__(*args, **kwargs)
+        CrewBaseMeta._initialize_crew_instance(instance, cls)
+        return instance
 
-            return types.MethodType(_close_mcp_server, self)
+    @staticmethod
+    def _initialize_crew_instance(instance: CrewInstance, cls: type) -> None:
+        """Initialize crew instance attributes and load configurations.
 
-        def get_mcp_tools(self, *tool_names: list[str]) -> list[BaseTool]:
-            if not self.mcp_server_params:
-                return []
+        Args:
+            instance: Crew instance to initialize.
+            cls: Crew class type.
+        """
+        instance._mcp_server_adapter = None
+        instance.load_configurations()
+        instance._all_functions = _get_all_functions(instance)
+        instance.map_all_agent_variables()
+        instance.map_all_task_variables()
 
-            from crewai_tools import MCPServerAdapter  # type: ignore[import-untyped]
-
-            adapter = getattr(self, "_mcp_server_adapter", None)
-            if not adapter:
-                self._mcp_server_adapter = MCPServerAdapter(
-                    self.mcp_server_params, connect_timeout=self.mcp_connect_timeout
-                )
-
-            return self._mcp_server_adapter.tools.filter_by_names(tool_names or None)
-
-        def load_configurations(self):
-            """Load agent and task configurations from YAML files."""
-            if isinstance(self.original_agents_config_path, str):
-                agents_config_path = (
-                    self.base_directory / self.original_agents_config_path
-                )
-                try:
-                    self.agents_config = self.load_yaml(agents_config_path)
-                except FileNotFoundError:
-                    logging.warning(
-                        f"Agent config file not found at {agents_config_path}. "
-                        "Proceeding with empty agent configurations."
-                    )
-                    self.agents_config = {}
-            else:
-                logging.warning(
-                    "No agent configuration path provided. Proceeding with empty agent configurations."
-                )
-                self.agents_config = {}
-
-            if isinstance(self.original_tasks_config_path, str):
-                tasks_config_path = (
-                    self.base_directory / self.original_tasks_config_path
-                )
-                try:
-                    self.tasks_config = self.load_yaml(tasks_config_path)
-                except FileNotFoundError:
-                    logging.warning(
-                        f"Task config file not found at {tasks_config_path}. "
-                        "Proceeding with empty task configurations."
-                    )
-                    self.tasks_config = {}
-            else:
-                logging.warning(
-                    "No task configuration path provided. Proceeding with empty task configurations."
-                )
-                self.tasks_config = {}
-
-        @staticmethod
-        def load_yaml(config_path: Path):
-            try:
-                with open(config_path, "r", encoding="utf-8") as file:
-                    return yaml.safe_load(file)
-            except FileNotFoundError:
-                print(f"File not found: {config_path}")
-                raise
-
-        def _get_all_functions(self):
-            return {
-                name: getattr(self, name)
-                for name in dir(self)
-                if callable(getattr(self, name))
-            }
-
-        def _filter_functions(
-            self, functions: dict[str, Callable], attribute: str
-        ) -> dict[str, Callable]:
-            return {
-                name: func
-                for name, func in functions.items()
-                if hasattr(func, attribute)
-            }
-
-        def map_all_agent_variables(self) -> None:
-            all_functions = self._get_all_functions()
-            llms = self._filter_functions(all_functions, "is_llm")
-            tool_functions = self._filter_functions(all_functions, "is_tool")
-            cache_handler_functions = self._filter_functions(
-                all_functions, "is_cache_handler"
-            )
-            callbacks = self._filter_functions(all_functions, "is_callback")
-
-            for agent_name, agent_info in self.agents_config.items():
-                self._map_agent_variables(
-                    agent_name,
-                    agent_info,
-                    llms,
-                    tool_functions,
-                    cache_handler_functions,
-                    callbacks,
-                )
-
-        def _map_agent_variables(
-            self,
-            agent_name: str,
-            agent_info: dict[str, Any],
-            llms: dict[str, Callable],
-            tool_functions: dict[str, Callable],
-            cache_handler_functions: dict[str, Callable],
-            callbacks: dict[str, Callable],
-        ) -> None:
-            if llm := agent_info.get("llm"):
-                try:
-                    self.agents_config[agent_name]["llm"] = llms[llm]()
-                except KeyError:
-                    self.agents_config[agent_name]["llm"] = llm
-
-            if tools := agent_info.get("tools"):
-                self.agents_config[agent_name]["tools"] = [
-                    tool_functions[tool]() for tool in tools
+        instance._original_functions = {
+            name: method
+            for name, method in cls.__dict__.items()
+            if any(
+                hasattr(method, attr)
+                for attr in [
+                    "is_task",
+                    "is_agent",
+                    "is_before_kickoff",
+                    "is_after_kickoff",
+                    "is_kickoff",
                 ]
-
-            if function_calling_llm := agent_info.get("function_calling_llm"):
-                try:
-                    self.agents_config[agent_name]["function_calling_llm"] = llms[
-                        function_calling_llm
-                    ]()
-                except KeyError:
-                    self.agents_config[agent_name]["function_calling_llm"] = (
-                        function_calling_llm
-                    )
-
-            if step_callback := agent_info.get("step_callback"):
-                self.agents_config[agent_name]["step_callback"] = callbacks[
-                    step_callback
-                ]()
-
-            if cache_handler := agent_info.get("cache_handler"):
-                self.agents_config[agent_name]["cache_handler"] = (
-                    cache_handler_functions[cache_handler]()
-                )
-
-        def map_all_task_variables(self) -> None:
-            all_functions = self._get_all_functions()
-            agents = self._filter_functions(all_functions, "is_agent")
-            tasks = self._filter_functions(all_functions, "is_task")
-            output_json_functions = self._filter_functions(
-                all_functions, "is_output_json"
             )
-            tool_functions = self._filter_functions(all_functions, "is_tool")
-            callback_functions = self._filter_functions(all_functions, "is_callback")
-            output_pydantic_functions = self._filter_functions(
-                all_functions, "is_output_pydantic"
+        }
+
+        instance._original_tasks = _filter_functions(
+            instance._original_functions, "is_task"
+        )
+        instance._original_agents = _filter_functions(
+            instance._original_functions, "is_agent"
+        )
+        instance._before_kickoff = _filter_functions(
+            instance._original_functions, "is_before_kickoff"
+        )
+        instance._after_kickoff = _filter_functions(
+            instance._original_functions, "is_after_kickoff"
+        )
+        instance._kickoff = _filter_functions(
+            instance._original_functions, "is_kickoff"
+        )
+
+        instance._after_kickoff["_close_mcp_server"] = instance._close_mcp_server
+
+
+def _close_mcp_server(
+    self: CrewInstance, _instance: CrewInstance, outputs: CrewOutput
+) -> CrewOutput:
+    """Stop MCP server adapter and return outputs.
+
+    Args:
+        self: Crew instance with MCP server adapter.
+        _instance: Crew instance (unused, required by callback signature).
+        outputs: Crew execution outputs.
+
+    Returns:
+        Unmodified crew outputs.
+    """
+    if self._mcp_server_adapter is not None:
+        try:
+            self._mcp_server_adapter.stop()
+        except Exception as e:
+            logging.warning(f"Error stopping MCP server: {e}")
+    return outputs
+
+
+def get_mcp_tools(self: Any, *tool_names: str) -> list[BaseTool]:
+    """Get MCP tools filtered by name.
+
+    Args:
+        self: Crew instance with MCP server configuration.
+        *tool_names: Optional tool names to filter by.
+
+    Returns:
+        List of filtered MCP tools, or empty list if no MCP server configured.
+    """
+    if not self.mcp_server_params:
+        return []
+
+    from crewai_tools import MCPServerAdapter  # type: ignore[import-untyped]
+
+    if self._mcp_server_adapter is None:
+        self._mcp_server_adapter = MCPServerAdapter(
+            self.mcp_server_params, connect_timeout=self.mcp_connect_timeout
+        )
+
+    return self._mcp_server_adapter.tools.filter_by_names(tool_names or None)
+
+
+def _load_config(
+    self: Any, config_path: str | None, config_type: str
+) -> dict[str, Any]:
+    """Load YAML config file or return empty dict if not found.
+
+    Args:
+        config_path: Relative path to config file.
+        config_type: Config type for logging (e.g., "agent", "task").
+
+    Returns:
+        Config dictionary or empty dict.
+    """
+    if isinstance(config_path, str):
+        full_path = self.base_directory / config_path
+        try:
+            return self.load_yaml(full_path)
+        except FileNotFoundError:
+            logging.warning(
+                f"{config_type.capitalize()} config file not found at {full_path}. "
+                f"Proceeding with empty {config_type} configurations."
+            )
+            return {}
+    else:
+        logging.warning(
+            f"No {config_type} configuration path provided. "
+            f"Proceeding with empty {config_type} configurations."
+        )
+        return {}
+
+
+def load_configurations(self: Any) -> None:
+    """Load agent and task YAML configurations.
+
+    Args:
+        self: Crew instance with configuration paths.
+    """
+    self.agents_config = self._load_config(self.original_agents_config_path, "agent")
+    self.tasks_config = self._load_config(self.original_tasks_config_path, "task")
+
+
+def load_yaml(config_path: Path) -> Any:
+    """Load and parse YAML file.
+
+    Args:
+        config_path: Path to YAML configuration file.
+
+    Returns:
+        Parsed YAML content.
+
+    Raises:
+        FileNotFoundError: If config file does not exist.
+    """
+    try:
+        with open(config_path, encoding="utf-8") as file:
+            return yaml.safe_load(file)
+    except FileNotFoundError:
+        print(f"File not found: {config_path}")
+        raise
+
+
+def _get_all_functions(self: Any) -> dict[str, Callable[..., Any]]:
+    """Return all non-dunder callable attributes.
+
+    Args:
+        self: Instance to inspect for callable attributes.
+
+    Returns:
+        Dictionary mapping attribute names to callable objects.
+    """
+    return {
+        name: getattr(self, name)
+        for name in dir(self)
+        if not (name.startswith("__") and name.endswith("__"))
+        and callable(getattr(self, name, None))
+    }
+
+
+def _filter_functions(
+    functions: dict[str, Callable[..., Any]], attribute: str
+) -> dict[str, Callable[..., Any]]:
+    """Filter functions by attribute presence.
+
+    Args:
+        functions: Dictionary of functions to filter.
+        attribute: Attribute name to check for.
+
+    Returns:
+        Dictionary containing only functions with the specified attribute.
+    """
+    return {name: func for name, func in functions.items() if hasattr(func, attribute)}
+
+
+def map_all_agent_variables(self: Any) -> None:
+    """Map agent configuration variables to callable instances.
+
+    Args:
+        self: Crew instance with agent configurations to map.
+    """
+    llms = _filter_functions(self._all_functions, "is_llm")
+    tool_functions = _filter_functions(self._all_functions, "is_tool")
+    cache_handler_functions = _filter_functions(self._all_functions, "is_cache_handler")
+    callbacks = _filter_functions(self._all_functions, "is_callback")
+
+    for agent_name, agent_info in self.agents_config.items():
+        self._map_agent_variables(
+            agent_name,
+            agent_info,
+            llms,
+            tool_functions,
+            cache_handler_functions,
+            callbacks,
+        )
+
+
+def _map_agent_variables(
+    self: Any,
+    agent_name: str,
+    agent_info: dict[str, Any],
+    llms: dict[str, Callable[..., Any]],
+    tool_functions: dict[str, Callable[..., Any]],
+    cache_handler_functions: dict[str, Callable[..., Any]],
+    callbacks: dict[str, Callable[..., Any]],
+) -> None:
+    """Resolve and map variables for a single agent.
+
+    Args:
+        self: Crew instance with agent configurations.
+        agent_name: Name of agent to configure.
+        agent_info: Agent configuration dictionary.
+        llms: Dictionary of available LLM providers.
+        tool_functions: Dictionary of available tools.
+        cache_handler_functions: Dictionary of available cache handlers.
+        callbacks: Dictionary of available callbacks.
+    """
+    if llm := agent_info.get("llm"):
+        try:
+            self.agents_config[agent_name]["llm"] = llms[llm]()
+        except KeyError:
+            self.agents_config[agent_name]["llm"] = llm
+
+    if tools := agent_info.get("tools"):
+        self.agents_config[agent_name]["tools"] = [
+            tool_functions[tool]() for tool in tools
+        ]
+
+    if function_calling_llm := agent_info.get("function_calling_llm"):
+        try:
+            self.agents_config[agent_name]["function_calling_llm"] = llms[
+                function_calling_llm
+            ]()
+        except KeyError:
+            self.agents_config[agent_name]["function_calling_llm"] = (
+                function_calling_llm
             )
 
-            for task_name, task_info in self.tasks_config.items():
-                self._map_task_variables(
-                    task_name,
-                    task_info,
-                    agents,
-                    tasks,
-                    output_json_functions,
-                    tool_functions,
-                    callback_functions,
-                    output_pydantic_functions,
-                )
+    if step_callback := agent_info.get("step_callback"):
+        self.agents_config[agent_name]["step_callback"] = callbacks[step_callback]()
 
-        def _map_task_variables(
-            self,
-            task_name: str,
-            task_info: dict[str, Any],
-            agents: dict[str, Callable],
-            tasks: dict[str, Callable],
-            output_json_functions: dict[str, Callable],
-            tool_functions: dict[str, Callable],
-            callback_functions: dict[str, Callable],
-            output_pydantic_functions: dict[str, Callable],
-        ) -> None:
-            if context_list := task_info.get("context"):
-                self.tasks_config[task_name]["context"] = [
-                    tasks[context_task_name]() for context_task_name in context_list
-                ]
+    if cache_handler := agent_info.get("cache_handler"):
+        self.agents_config[agent_name]["cache_handler"] = cache_handler_functions[
+            cache_handler
+        ]()
 
-            if tools := task_info.get("tools"):
-                self.tasks_config[task_name]["tools"] = [
-                    tool_functions[tool]() for tool in tools
-                ]
 
-            if agent_name := task_info.get("agent"):
-                self.tasks_config[task_name]["agent"] = agents[agent_name]()
+def map_all_task_variables(self: Any) -> None:
+    """Map task configuration variables to callable instances.
 
-            if output_json := task_info.get("output_json"):
-                self.tasks_config[task_name]["output_json"] = output_json_functions[
-                    output_json
-                ]
+    Args:
+        self: Crew instance with task configurations to map.
+    """
+    agents = _filter_functions(self._all_functions, "is_agent")
+    tasks = _filter_functions(self._all_functions, "is_task")
+    output_json_functions = _filter_functions(self._all_functions, "is_output_json")
+    tool_functions = _filter_functions(self._all_functions, "is_tool")
+    callback_functions = _filter_functions(self._all_functions, "is_callback")
+    output_pydantic_functions = _filter_functions(
+        self._all_functions, "is_output_pydantic"
+    )
 
-            if output_pydantic := task_info.get("output_pydantic"):
-                self.tasks_config[task_name]["output_pydantic"] = (
-                    output_pydantic_functions[output_pydantic]
-                )
+    for task_name, task_info in self.tasks_config.items():
+        self._map_task_variables(
+            task_name,
+            task_info,
+            agents,
+            tasks,
+            output_json_functions,
+            tool_functions,
+            callback_functions,
+            output_pydantic_functions,
+        )
 
-            if callbacks := task_info.get("callbacks"):
-                self.tasks_config[task_name]["callbacks"] = [
-                    callback_functions[callback]() for callback in callbacks
-                ]
 
-            if guardrail := task_info.get("guardrail"):
-                self.tasks_config[task_name]["guardrail"] = guardrail
+def _map_task_variables(
+    self: Any,
+    task_name: str,
+    task_info: dict[str, Any],
+    agents: dict[str, Callable[..., Any]],
+    tasks: dict[str, Callable[..., Any]],
+    output_json_functions: dict[str, Callable[..., Any]],
+    tool_functions: dict[str, Callable[..., Any]],
+    callback_functions: dict[str, Callable[..., Any]],
+    output_pydantic_functions: dict[str, Callable[..., Any]],
+) -> None:
+    """Resolve and map variables for a single task.
 
-    # Include base class (qual)name in the wrapper class (qual)name.
-    WrappedClass.__name__ = CrewBase.__name__ + "(" + cls.__name__ + ")"
-    WrappedClass.__qualname__ = CrewBase.__qualname__ + "(" + cls.__name__ + ")"
-    WrappedClass._crew_name = cls.__name__
+    Args:
+        self: Crew instance with task configurations.
+        task_name: Name of task to configure.
+        task_info: Task configuration dictionary.
+        agents: Dictionary of available agents.
+        tasks: Dictionary of available tasks.
+        output_json_functions: Dictionary of available JSON output schemas.
+        tool_functions: Dictionary of available tools.
+        callback_functions: Dictionary of available callbacks.
+        output_pydantic_functions: Dictionary of available Pydantic output schemas.
+    """
+    if context_list := task_info.get("context"):
+        self.tasks_config[task_name]["context"] = [
+            tasks[context_task_name]() for context_task_name in context_list
+        ]
 
-    return cast(T, WrappedClass)
+    if tools := task_info.get("tools"):
+        self.tasks_config[task_name]["tools"] = [
+            tool_functions[tool]() for tool in tools
+        ]
+
+    if agent_name := task_info.get("agent"):
+        self.tasks_config[task_name]["agent"] = agents[agent_name]()
+
+    if output_json := task_info.get("output_json"):
+        self.tasks_config[task_name]["output_json"] = output_json_functions[output_json]
+
+    if output_pydantic := task_info.get("output_pydantic"):
+        self.tasks_config[task_name]["output_pydantic"] = output_pydantic_functions[
+            output_pydantic
+        ]
+
+    if callbacks := task_info.get("callbacks"):
+        self.tasks_config[task_name]["callbacks"] = [
+            callback_functions[callback]() for callback in callbacks
+        ]
+
+    if guardrail := task_info.get("guardrail"):
+        self.tasks_config[task_name]["guardrail"] = guardrail
+
+
+def CrewBase(cls: type) -> type:  # noqa: N802
+    """Apply CrewBaseMeta metaclass to a class for decorator syntax compatibility.
+
+    Args:
+        cls: Class to apply metaclass to.
+
+    Returns:
+        New class with CrewBaseMeta metaclass applied.
+    """
+    if isinstance(cls, CrewBaseMeta):
+        return cls
+
+    namespace = {
+        key: value
+        for key, value in cls.__dict__.items()
+        if not key.startswith("__")
+        or key in ("__module__", "__qualname__", "__annotations__")
+    }
+
+    return CrewBaseMeta(cls.__name__, cls.__bases__, namespace)

src/crewai/project/wrappers.py

@@ -8,6 +8,7 @@ from typing import TYPE_CHECKING, Any, Generic, ParamSpec, Protocol, Self, TypeV
 
 if TYPE_CHECKING:
     from crewai import Agent, Task
+    from crewai.crews.crew_output import CrewOutput
 
 P = ParamSpec("P")
 R = TypeVar("R")
@@ -37,13 +38,22 @@ def _copy_function_metadata(wrapper: Any, func: Callable[..., Any]) -> None:
 class CrewInstance(Protocol):
     """Protocol for crew class instances with required attributes."""
 
+    _mcp_server_adapter: Any
+    _all_functions: dict[str, Callable[..., Any]]
+    _original_functions: dict[str, Callable[..., Any]]
     _original_tasks: dict[str, Callable[[Self], Task]]
     _original_agents: dict[str, Callable[[Self], Agent]]
     _before_kickoff: dict[str, Callable[..., Any]]
     _after_kickoff: dict[str, Callable[..., Any]]
+    _kickoff: dict[str, Callable[..., Any]]
     agents: list[Agent]
     tasks: list[Task]
 
+    def load_configurations(self) -> None: ...
+    def map_all_agent_variables(self) -> None: ...
+    def map_all_task_variables(self) -> None: ...
+    def _close_mcp_server(self, instance: Self, outputs: CrewOutput) -> CrewOutput: ...
+
 
 class DecoratedMethod(Generic[P, R]):
     """Base wrapper for methods with decorator metadata.