diff --git a/basedpyright-code-budget.json b/basedpyright-code-budget.json
index da788bf1ce3..9997e5dc0c6 100644
--- a/basedpyright-code-budget.json
+++ b/basedpyright-code-budget.json
@@ -123,7 +123,7 @@
     "limit": 5
   },
   "reportUnnecessaryIsInstance": {
-    "limit": 826
+    "limit": 823
   },
   "reportUntypedBaseClass": {
     "limit": 0
diff --git a/litellm/llms/openai/responses/guardrail_translation/handler.py b/litellm/llms/openai/responses/guardrail_translation/handler.py
index 1530c154e93..caa20207a15 100644
--- a/litellm/llms/openai/responses/guardrail_translation/handler.py
+++ b/litellm/llms/openai/responses/guardrail_translation/handler.py
@@ -37,7 +37,7 @@ from typing import TYPE_CHECKING, Any, Final, Union, cast
 
 from openai.types.responses.response_function_tool_call import ResponseFunctionToolCall
 from openai.types.responses.tool_param import FunctionToolParam
-from pydantic import BaseModel, TypeAdapter
+from pydantic import BaseModel, TypeAdapter, ValidationError
 from typing_extensions import ReadOnly, TypedDict
 
 from litellm._logging import verbose_proxy_logger
@@ -110,6 +110,88 @@ class ResponsesStreamChunk(TypedDict, total=False):
     content_index: ReadOnly[int]
 
 
+_TOOL_TYPES_NOT_SENT_TO_GUARDRAIL: Final = frozenset(
+    {"web_search", "web_search_preview", "computer_use", "image_generation", "shell"}
+)
+
+
+_NAMESPACE_MEMBERS: Final = TypeAdapter(tuple[Mapping[str, object], ...])
+
+
+def _namespace_members(tool: Mapping[str, object]) -> tuple[Mapping[str, object], ...] | None:
+    """``None`` when the namespace has no member list and is flattened to one function named after it."""
+    raw_members: Final = tool.get("tools")
+    if not isinstance(raw_members, Sequence) or isinstance(raw_members, (str, bytes)):
+        return None
+    try:
+        return _NAMESPACE_MEMBERS.validate_python(raw_members)
+    except ValidationError:
+        return ()
+
+
+def _is_function_member(member: Mapping[str, object]) -> bool:
+    return member.get("type") == "function"
+
+
+def _qualified_member_name(namespace: str, member: Mapping[str, object]) -> str:
+    return f"{namespace}__{member.get('name') or ''}"
+
+
+def _namespace_function_names(tool: Mapping[str, object]) -> tuple[str, ...]:
+    namespace: Final = str(tool.get("name") or "")
+    members: Final = _namespace_members(tool)
+    if members is None:
+        return (namespace,)
+    return tuple(_qualified_member_name(namespace, member) for member in members if _is_function_member(member))
+
+
+def _flattened_function_names(tools: Sequence[Mapping[str, object]]) -> tuple[str, ...]:
+    """Names the guardrail sees for ``tools`` once flattened to Chat Completions format."""
+    top_level: Final = tuple(
+        str(tool.get("name") or "") for tool in tools if tool.get("type") in ("function", "custom")
+    )
+    nested: Final = tuple(
+        name for tool in tools if tool.get("type") == "namespace" for name in _namespace_function_names(tool)
+    )
+    return top_level + nested
+
+
+def _merge_namespace_tool(
+    tool: Mapping[str, object], remapped_functions: Mapping[str, Mapping[str, object]]
+) -> Mapping[str, object] | None:
+    namespace: Final = str(tool.get("name") or "")
+    members: Final = _namespace_members(tool)
+    if members is None:
+        return tool if namespace in remapped_functions else None
+    surviving: Final = tuple(
+        member
+        for member in members
+        if not _is_function_member(member) or _qualified_member_name(namespace, member) in remapped_functions
+    )
+    if len(surviving) == len(members):
+        return tool
+    if not any(_is_function_member(member) for member in surviving):
+        return None
+    return {**tool, "tools": [*surviving]}  # mutable-ok: request tools are JSON dicts sent to the provider
+
+
+def _merge_original_tool(
+    tool: Mapping[str, object],
+    remapped_functions: Mapping[str, Mapping[str, object]],
+    remapped_passthrough: Sequence[Mapping[str, object]],
+) -> Mapping[str, object] | None:
+    tool_type: Final = tool.get("type")
+    if tool_type in _TOOL_TYPES_NOT_SENT_TO_GUARDRAIL:
+        return tool
+    if tool_type == "function":
+        return remapped_functions.get(str(tool.get("name") or ""))
+    if tool_type == "custom":
+        return tool if str(tool.get("name") or "") in remapped_functions else None
+    if tool_type == "namespace":
+        return _merge_namespace_tool(tool, remapped_functions)
+    return tool if tool in remapped_passthrough else None
+
+
 def _next_stream_sequence_number(responses_so_far: Sequence[Any] | None) -> int:
     sequence_numbers: Final = (
         item.get("sequence_number") if isinstance(item, dict) else getattr(item, "sequence_number", None)
@@ -297,32 +379,37 @@ class OpenAIResponsesHandler(BaseTranslation):
 
     def _merge_tools_after_guardrail(
         self,
-        original_tools: list[dict[str, object]],
+        original_tools: Sequence[Mapping[str, object]],
         remapped: list[dict[str, object]],
-    ) -> list[dict[str, object]]:
+    ) -> Sequence[Mapping[str, object]]:
         """
-        Merge remapped guardrailed tools with original tools that were not sent
-        to the guardrail (e.g. web_search, web_search_preview), preserving order.
-        Tools a guardrail appended (``remapped`` longer than ``original_tools``)
-        have no original slot and are kept so an injected tool is not dropped.
+        Rebuild the Responses tool list from ``original_tools`` and apply only the
+        guardrail's delta: tools it dropped are removed (namespace members
+        individually), tools it appended are kept at the end, and tools that never
+        reach the guardrail (web_search, computer_use, ...) stay untouched.
+        Namespace tools keep their wrapper and member names instead of the
+        ``namespace__tool`` functions the guardrail saw.
         """
         if not original_tools:
             return remapped
-        result: Final[list[dict[str, object]]] = []
-        j = 0
-        for tool in original_tools:
-            if isinstance(tool, dict) and tool.get("type") in (
-                "web_search",
-                "web_search_preview",
-            ):
-                result.append(tool)
-            else:
-                if j < len(remapped):
-                    result.append(remapped[j])
-                    j += 1
-        # Keep guardrail-appended tools that matched no original slot above.
-        result.extend(remapped[j:])
-        return result
+        remapped_functions: Final = MappingProxyType(
+            {str(tool.get("name") or ""): tool for tool in remapped if tool.get("type") == "function"}
+        )
+        remapped_passthrough: Final = tuple(tool for tool in remapped if tool.get("type") != "function")
+        original_function_names: Final = frozenset(_flattened_function_names(original_tools))
+        kept: Final = tuple(
+            merged
+            for tool in original_tools
+            for merged in (_merge_original_tool(tool, remapped_functions, remapped_passthrough),)
+            if merged is not None
+        )
+        appended: Final = tuple(
+            tool
+            for tool in remapped
+            if (tool.get("type") == "function" and str(tool.get("name") or "") not in original_function_names)
+            or (tool.get("type") != "function" and tool not in original_tools)
+        )
+        return [*kept, *appended]  # mutable-ok: request tools are JSON dicts sent to the provider
 
     def _apply_guardrailed_tools_to_data(
         self,
diff --git a/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py b/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py
index 315b6948bd8..7e624f39c53 100644
--- a/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py
+++ b/tests/test_litellm/llms/openai/responses/test_openai_responses_guardrail_handler.py
@@ -1323,6 +1323,125 @@ class TestOpenAIResponsesHandlerToolInjection:
         assert "injected_tool" in names
 
 
+class ToolDroppingGuardrail(CustomGuardrail):
+    """Guardrail that removes one flattened function tool by name."""
+
+    def __init__(self, drop: str, **kwargs):
+        super().__init__(**kwargs)
+        self.drop = drop
+
+    async def apply_guardrail(
+        self,
+        inputs: GenericGuardrailAPIInputs,
+        request_data: dict,
+        input_type: Literal["request", "response"],
+        logging_obj: Optional[Any] = None,
+    ) -> GenericGuardrailAPIInputs:
+        return {
+            **inputs,
+            "tools": [t for t in inputs.get("tools") or [] if t["function"]["name"] != self.drop],
+        }
+
+
+CODEX_NAMESPACE_TOOL = {
+    "type": "namespace",
+    "name": "mcp__confluence",
+    "description": "Tools from the confluence MCP server",
+    "tools": [
+        {
+            "type": "function",
+            "name": "confluence_get_page",
+            "description": "Get a page",
+            "parameters": {"type": "object", "properties": {"page_id": {"type": "string"}}},
+        },
+        {
+            "type": "function",
+            "name": "confluence_search",
+            "description": "Search",
+            "parameters": {"type": "object", "properties": {"query": {"type": "string"}}},
+        },
+    ],
+}
+
+
+class TestOpenAIResponsesHandlerNamespaceTools:
+    """Regression for #39183: a guardrail on /v1/responses must not rewrite Codex
+    namespace MCP tools into flat ``namespace__tool`` functions."""
+
+    @pytest.mark.asyncio
+    async def test_namespace_tool_survives_tool_appending_guardrail(self):
+        handler = OpenAIResponsesHandler()
+        data = {
+            "input": [{"role": "user", "content": "fetch page 1", "type": "message"}],
+            "tools": [
+                {"type": "function", "name": "shell", "parameters": {"type": "object", "properties": {}}},
+                CODEX_NAMESPACE_TOOL,
+            ],
+            "model": "gpt-5.3-codex",
+        }
+
+        result = await handler.process_input_messages(data, ToolAppendingGuardrail(guardrail_name="test"))
+
+        assert [t["type"] for t in result["tools"]] == ["function", "namespace", "function"]
+        assert result["tools"][0]["name"] == "shell"
+        assert result["tools"][1] == CODEX_NAMESPACE_TOOL
+        assert result["tools"][2]["name"] == "injected_tool"
+        assert not any(t["name"].startswith("mcp__confluence__") for t in result["tools"])
+
+    @pytest.mark.asyncio
+    async def test_unchanged_guardrail_leaves_custom_mcp_and_memberless_namespace_tools_as_is(self):
+        handler = OpenAIResponsesHandler()
+        tools = [
+            {"type": "custom", "name": "apply_patch", "description": "Apply a patch"},
+            {"type": "mcp", "server_label": "docs", "server_url": "https://mcp.example.com"},
+            {"type": "namespace", "name": "mcp__flat", "description": "Flattened to one function"},
+        ]
+        data = {
+            "input": [{"role": "user", "content": "fetch page 1", "type": "message"}],
+            "tools": [dict(t) for t in tools],
+            "model": "gpt-5.3-codex",
+        }
+
+        result = await handler.process_input_messages(data, MockPassThroughGuardrail(guardrail_name="test"))
+
+        assert result["tools"] == tools
+
+    @pytest.mark.asyncio
+    async def test_guardrail_can_still_drop_a_single_namespace_member(self):
+        handler = OpenAIResponsesHandler()
+        data = {
+            "input": [{"role": "user", "content": "fetch page 1", "type": "message"}],
+            "tools": [CODEX_NAMESPACE_TOOL],
+            "model": "gpt-5.3-codex",
+        }
+
+        result = await handler.process_input_messages(
+            data, ToolDroppingGuardrail(drop="mcp__confluence__confluence_search", guardrail_name="test")
+        )
+
+        assert len(result["tools"]) == 1
+        namespace_tool = result["tools"][0]
+        assert namespace_tool["type"] == "namespace"
+        assert namespace_tool["name"] == "mcp__confluence"
+        assert [t["name"] for t in namespace_tool["tools"]] == ["confluence_get_page"]
+
+    @pytest.mark.asyncio
+    async def test_namespace_tool_removed_when_guardrail_drops_every_member(self):
+        handler = OpenAIResponsesHandler()
+        single_member = {**CODEX_NAMESPACE_TOOL, "tools": CODEX_NAMESPACE_TOOL["tools"][:1]}
+        data = {
+            "input": [{"role": "user", "content": "fetch page 1", "type": "message"}],
+            "tools": [{"type": "web_search_preview"}, single_member],
+            "model": "gpt-5.3-codex",
+        }
+
+        result = await handler.process_input_messages(
+            data, ToolDroppingGuardrail(drop="mcp__confluence__confluence_get_page", guardrail_name="test")
+        )
+
+        assert result["tools"] == [{"type": "web_search_preview"}]
+
+
 class TestBuildBlockSseChunks:
     """build_block_sse_chunks turns a streaming ModifyResponseException into 200 SSE events"""
 
diff --git a/type-discipline-budget.json b/type-discipline-budget.json
index 52cb9628252..07bc874880f 100644
--- a/type-discipline-budget.json
+++ b/type-discipline-budget.json
@@ -1,9 +1,9 @@
 {
   "LIT001": {
-    "limit": 22364
+    "limit": 22352
   },
   "LIT002": {
-    "limit": 26777
+    "limit": 26774
   },
   "LIT003": {
     "limit": 269
@@ -27,7 +27,7 @@
     "limit": 0
   },
   "LIT010": {
-    "limit": 16507
+    "limit": 16504
   },
   "LIT011": {
     "limit": 5535