diff --git a/src/backend/base/langflow/custom/custom_component/component.py b/src/backend/base/langflow/custom/custom_component/component.py
index 5e5c14a3c..a5e51801b 100644
--- a/src/backend/base/langflow/custom/custom_component/component.py
+++ b/src/backend/base/langflow/custom/custom_component/component.py
@@ -1,5 +1,5 @@
 import inspect
-from typing import TYPE_CHECKING, Any, AsyncIterator, Callable, ClassVar, Generator, Iterator, List, Optional, Union
+from typing import Any, AsyncIterator, Callable, ClassVar, Generator, Iterator, List, Optional, Union
 from uuid import UUID
 
 import yaml
@@ -13,9 +13,6 @@ from langflow.template.field.base import UNDEFINED, Output
 
 from .custom_component import CustomComponent
 
-if TYPE_CHECKING:
-    from langflow.graph.vertex.base import Vertex
-
 
 def recursive_serialize_or_str(obj):
     try:
@@ -47,6 +44,8 @@ class Component(CustomComponent):
         self._inputs: dict[str, InputTypes] = {}
         self._results: dict[str, Any] = {}
         self._attributes: dict[str, Any] = {}
+        if not hasattr(self, "trace_type"):
+            self.trace_type = "chain"
         if self.inputs is not None:
             self.map_inputs(self.inputs)
 
@@ -57,12 +56,6 @@ class Component(CustomComponent):
             return self.__dict__["_inputs"][name].value
         raise AttributeError(f"{name} not found in {self.__class__.__name__}")
 
-    # def __getattribute__(self, name: str) -> Any:
-    #     try:
-    #         return super().__getattribute__(name)
-    #     except AttributeError:
-    #         return self.__getattr__(name)
-
     def map_inputs(self, inputs: List[InputTypes]):
         self.inputs = inputs
         for input_ in inputs:
@@ -105,15 +98,40 @@ class Component(CustomComponent):
         for output in self.outputs:
             setattr(self, output.name, output)
 
-    async def build_results(self, vertex: "Vertex"):
+    def get_trace_as_inputs(self):
+        return {
+            input_.name: input_.value
+            for input_ in self.inputs
+            if hasattr(input_, "trace_as_input") and input_.trace_as_input
+        }
+
+    def get_trace_as_metadata(self):
+        return {
+            input_.name: input_.value
+            for input_ in self.inputs
+            if hasattr(input_, "trace_as_metadata") and input_.trace_as_metadata
+        }
+
+    async def build_results(self):
+        inputs = self.get_trace_as_inputs()
+        metadata = self.get_trace_as_metadata()
+        with self.tracing_service.trace_context(
+            f"{self.display_name} ({self.vertex.id})", self.trace_type, inputs, metadata
+        ):
+            _results, _artifacts = await self._build_results()
+            self.tracing_service.set_outputs(_results)
+
+        return _results, _artifacts
+
+    async def _build_results(self):
         _results = {}
         _artifacts = {}
         if hasattr(self, "outputs"):
-            self._set_outputs(vertex.outputs)
+            self._set_outputs(self.vertex.outputs)
             for output in self.outputs:
                 # Build the output if it's connected to some other vertex
                 # or if it's not connected to any vertex
-                if not vertex.outgoing_edges or output.name in vertex.edges_source_names:
+                if not self.vertex.outgoing_edges or output.name in self.vertex.edges_source_names:
                     if output.method is None:
                         raise ValueError(f"Output {output.name} does not have a method defined.")
                     method: Callable = getattr(self, output.method)
@@ -124,8 +142,12 @@ class Component(CustomComponent):
                         # If the method is asynchronous, we need to await it
                         if inspect.iscoroutinefunction(method):
                             result = await result
-                        if isinstance(result, Message) and result.flow_id is None and vertex.graph.flow_id is not None:
-                            result.set_flow_id(vertex.graph.flow_id)
+                        if (
+                            isinstance(result, Message)
+                            and result.flow_id is None
+                            and self.vertex.graph.flow_id is not None
+                        ):
+                            result.set_flow_id(self.vertex.graph.flow_id)
                         _results[output.name] = result
                         output.value = result
                         custom_repr = self.custom_repr()
@@ -155,6 +177,8 @@ class Component(CustomComponent):
                         _artifacts[output.name] = artifact
         self._artifacts = _artifacts
         self._results = _results
+        if self.tracing_service:
+            self.tracing_service.set_outputs(_results)
         return _results, _artifacts
 
     def custom_repr(self):
diff --git a/src/backend/base/langflow/custom/custom_component/custom_component.py b/src/backend/base/langflow/custom/custom_component/custom_component.py
index c9bc1bfdf..de588a622 100644
--- a/src/backend/base/langflow/custom/custom_component/custom_component.py
+++ b/src/backend/base/langflow/custom/custom_component/custom_component.py
@@ -26,6 +26,7 @@ if TYPE_CHECKING:
     from langflow.graph.graph.base import Graph
     from langflow.graph.vertex.base import Vertex
     from langflow.services.storage.service import StorageService
+    from langflow.services.tracing.service import TracingService
 
 
 LoggableType = Union[str, dict, list, int, float, bool, None, Data, Message]
@@ -82,6 +83,7 @@ class CustomComponent(BaseComponent):
     """The status of the component. This is displayed on the frontend. Defaults to None."""
     _flows_data: Optional[List[Data]] = None
     _logs: List[Log] = []
+    tracing_service: Optional["TracingService"] = None
 
     def update_state(self, name: str, value: Any):
         if not self.vertex: