diff --git a/litellm/responses/main.py b/litellm/responses/main.py
index 8f524690be1..7105f1ae6fb 100644
--- a/litellm/responses/main.py
+++ b/litellm/responses/main.py
@@ -181,6 +181,7 @@ async def aresponses_api_with_mcp(
     ) = await LiteLLM_Proxy_MCP_Handler._process_mcp_tools_without_openai_transform(
         user_api_key_auth=user_api_key_auth,
         mcp_tools_with_litellm_proxy=mcp_tools_with_litellm_proxy,
+        litellm_trace_id=kwargs.get("litellm_trace_id"),
     )
     openai_tools = LiteLLM_Proxy_MCP_Handler._transform_mcp_tools_to_openai(
         original_mcp_tools
diff --git a/litellm/responses/mcp/litellm_proxy_mcp_handler.py b/litellm/responses/mcp/litellm_proxy_mcp_handler.py
index 297ccf4355e..805a1958552 100644
--- a/litellm/responses/mcp/litellm_proxy_mcp_handler.py
+++ b/litellm/responses/mcp/litellm_proxy_mcp_handler.py
@@ -6,10 +6,10 @@ from typing import (
     Dict,
     Iterable,
     List,
+    Literal,
     Optional,
     Tuple,
     Union,
-    Literal,
 )
 
 from litellm._logging import verbose_logger
@@ -29,6 +29,7 @@ from litellm.utils import Rules, function_setup
 
 if TYPE_CHECKING:
     from mcp.types import Tool as MCPTool
+
     from litellm.proxy.utils import ProxyLogging
 else:
     MCPTool = Any
@@ -97,6 +98,7 @@ class LiteLLM_Proxy_MCP_Handler:
     async def _get_mcp_tools_from_manager(
         user_api_key_auth: Any,
         mcp_tools_with_litellm_proxy: Optional[Iterable[ToolParam]],
+        litellm_trace_id: Optional[str] = None,
     ) -> tuple[List[MCPTool], List[str]]:
         """
         Get available tools from the MCP server manager.
@@ -109,13 +111,13 @@ class LiteLLM_Proxy_MCP_Handler:
             List of MCP tools
             List names of allowed MCP servers
         """
-        from litellm.proxy._experimental.mcp_server.server import (
-            _get_tools_from_mcp_servers,
-            _get_allowed_mcp_servers_from_mcp_server_names,
-        )
         from litellm.proxy._experimental.mcp_server.mcp_server_manager import (
             global_mcp_server_manager,
         )
+        from litellm.proxy._experimental.mcp_server.server import (
+            _get_allowed_mcp_servers_from_mcp_server_names,
+            _get_tools_from_mcp_servers,
+        )
 
         mcp_servers: List[str] = []
         if mcp_tools_with_litellm_proxy:
@@ -136,6 +138,7 @@ class LiteLLM_Proxy_MCP_Handler:
             mcp_server_auth_headers=None,
             log_list_tools_to_spendlogs=True,
             list_tools_log_source="responses",
+            litellm_trace_id=litellm_trace_id,
         )
         allowed_mcp_server_ids = (
             await global_mcp_server_manager.get_allowed_mcp_servers(user_api_key_auth)
@@ -239,7 +242,9 @@ class LiteLLM_Proxy_MCP_Handler:
 
     @staticmethod
     async def _process_mcp_tools_to_openai_format(
-        user_api_key_auth: Any, mcp_tools_with_litellm_proxy: List[ToolParam]
+        user_api_key_auth: Any,
+        mcp_tools_with_litellm_proxy: List[ToolParam],
+        litellm_trace_id: Optional[str] = None,
     ) -> tuple[List[Any], dict[str, str]]:
         """
         Centralized method to process MCP tools through the complete pipeline.
@@ -247,6 +252,7 @@ class LiteLLM_Proxy_MCP_Handler:
         Args:
             user_api_key_auth: User authentication info for access control
             mcp_tools_with_litellm_proxy: ToolParam objects with server_url starting with "litellm_proxy"
+            litellm_trace_id: Optional trace ID for linking list_mcp_tools spend logs to parent request
 
         Returns:
             List of tools in OpenAI format ready to be sent to the LLM
@@ -258,6 +264,7 @@ class LiteLLM_Proxy_MCP_Handler:
         ) = await LiteLLM_Proxy_MCP_Handler._process_mcp_tools_without_openai_transform(
             user_api_key_auth,
             mcp_tools_with_litellm_proxy,
+            litellm_trace_id=litellm_trace_id,
         )
 
         openai_tools = LiteLLM_Proxy_MCP_Handler._transform_mcp_tools_to_openai(
@@ -268,7 +275,9 @@ class LiteLLM_Proxy_MCP_Handler:
 
     @staticmethod
     async def _process_mcp_tools_without_openai_transform(
-        user_api_key_auth: Any, mcp_tools_with_litellm_proxy: List[ToolParam]
+        user_api_key_auth: Any,
+        mcp_tools_with_litellm_proxy: List[ToolParam],
+        litellm_trace_id: Optional[str] = None,
     ) -> tuple[List[Any], dict[str, str]]:
         """
         Process MCP tools through filtering and deduplication pipeline without OpenAI transformation.
@@ -291,6 +300,7 @@ class LiteLLM_Proxy_MCP_Handler:
         ) = await LiteLLM_Proxy_MCP_Handler._get_mcp_tools_from_manager(
             user_api_key_auth=user_api_key_auth,
             mcp_tools_with_litellm_proxy=mcp_tools_with_litellm_proxy,
+            litellm_trace_id=litellm_trace_id,
         )
 
         # Step 2: Filter tools based on allowed_tools parameter
@@ -495,14 +505,13 @@ class LiteLLM_Proxy_MCP_Handler:
         """Execute tool calls and return results."""
         from fastapi import HTTPException
 
+        from litellm._uuid import uuid
         from litellm.exceptions import BlockedPiiEntityError, GuardrailRaisedException
         from litellm.proxy._experimental.mcp_server.mcp_server_manager import (
             global_mcp_server_manager,
         )
         from litellm.proxy.proxy_server import proxy_logging_obj
 
-        from litellm._uuid import uuid
-
         tool_results = []
         tool_call_id: Optional[str] = None
         rules_obj = Rules()
@@ -1025,7 +1034,6 @@ class LiteLLM_Proxy_MCP_Handler:
             List of MCP tool execution events for streaming
         """
         from litellm._uuid import uuid
-
         from litellm.responses.mcp.mcp_streaming_iterator import create_mcp_call_events
 
         tool_execution_events: List[Any] = []
@@ -1108,8 +1116,8 @@ class LiteLLM_Proxy_MCP_Handler:
         """Add custom output elements to the final response for MCP tool execution."""
         # Import the required classes for creating output items
         import json
-        from litellm._uuid import uuid
 
+        from litellm._uuid import uuid
         from litellm.types.responses.main import GenericResponseOutputItem, OutputText
 
         # Create output element for initial MCP tools