LangChain Tool SubComponent Gating

newrelic/hooks/mlmodel_langchain.py

@@ -575,11 +575,12 @@ def wrap_tool_sync_run(wrapped, instance, args, kwargs):
     except Exception:
         filtered_tool_input = tool_input
 
-    agentic_subcomponent_data = {"type": "APM-AI_TOOL", "name": tool_name}
-
     ft = FunctionTrace(name=f"{wrapped.__name__}/{tool_name}", group="Llm/tool/LangChain")
     ft.__enter__()
-    ft._add_agent_attribute("subcomponent", json.dumps(agentic_subcomponent_data))
+    # Subcomponent attribute is only added when the tool executes locally
+    if _is_local_tool(instance):
+        agentic_subcomponent_data = {"type": "APM-AI_TOOL", "name": tool_name}
+        ft._add_agent_attribute("subcomponent", json.dumps(agentic_subcomponent_data))
     linking_metadata = get_trace_linking_metadata()
     try:
         return_val = wrapped(**run_args)
@@ -639,11 +640,12 @@ async def wrap_tool_async_run(wrapped, instance, args, kwargs):
     except Exception:
         filtered_tool_input = tool_input
 
-    agentic_subcomponent_data = {"type": "APM-AI_TOOL", "name": tool_name}
-
     ft = FunctionTrace(name=f"{wrapped.__name__}/{tool_name}", group="Llm/tool/LangChain")
     ft.__enter__()
-    ft._add_agent_attribute("subcomponent", json.dumps(agentic_subcomponent_data))
+    # Subcomponent attribute is only added when the tool executes locally
+    if _is_local_tool(instance):
+        agentic_subcomponent_data = {"type": "APM-AI_TOOL", "name": tool_name}
+        ft._add_agent_attribute("subcomponent", json.dumps(agentic_subcomponent_data))
     linking_metadata = get_trace_linking_metadata()
     try:
         return_val = await wrapped(**run_args)
@@ -680,6 +682,31 @@ async def wrap_tool_async_run(wrapped, instance, args, kwargs):
     return return_val
 
 
+# Known modules whose tools execute remotely.
+_REMOTE_TOOL_MODULE_PREFIXES = ("langchain_mcp_adapters", "langgraph.pregel.remote")
+
+
+def _is_local_tool(instance):
+    """
+    Best effort check that a LangChain tool executes locally.
+
+    Returns False only for known remote tools.
+    """
+    try:
+        # StructuredTool holds the underlying callable in the func or coroutine attributes.
+        # Custom BaseTool subclasses hold their logic on the class itself.
+        candidates = (getattr(instance, "func", None), getattr(instance, "coroutine", None), type(instance))
+        for candidate in candidates:
+            module = getattr(candidate, "__module__", "") or ""
+            if module.startswith(_REMOTE_TOOL_MODULE_PREFIXES):
+                return False
+    except Exception:
+        pass
+
+    # If we can't prove it was a remote tool, assume it was local.
+    return True
+
+
 def _capture_tool_info(instance, wrapped, args, kwargs):
     run_args = bind_args(wrapped, args, kwargs)
 

tests/mlmodel_langchain/cassette.yaml

@@ -110,13 +110,12 @@ interactions:
     body:
       string: '{"id": "chatcmpl-DyjwCWB6oPS6gcxdy4b9JW4Ey6Lv5", "object": "chat.completion",
         "created": 1783368636, "model": "gpt-3.5-turbo-0125", "choices": [{"index":
-        0, "message": {"role": "assistant", "content": "Hello!",
-        "refusal": null, "annotations": []}, "logprobs": null, "finish_reason": "stop"}],
-        "usage": {"prompt_tokens": 107, "completion_tokens": 2, "total_tokens": 109,
-        "prompt_tokens_details": {"cached_tokens": 0, "audio_tokens": 0}, "completion_tokens_details":
-        {"reasoning_tokens": 0, "audio_tokens": 0, "accepted_prediction_tokens": 0,
-        "rejected_prediction_tokens": 0}}, "service_tier": "default", "system_fingerprint":
-        null}'
+        0, "message": {"role": "assistant", "content": "Hello!", "refusal": null,
+        "annotations": []}, "logprobs": null, "finish_reason": "stop"}], "usage":
+        {"prompt_tokens": 107, "completion_tokens": 2, "total_tokens": 109, "prompt_tokens_details":
+        {"cached_tokens": 0, "audio_tokens": 0}, "completion_tokens_details": {"reasoning_tokens":
+        0, "audio_tokens": 0, "accepted_prediction_tokens": 0, "rejected_prediction_tokens":
+        0}}, "service_tier": "default", "system_fingerprint": null}'
     headers:
       access-control-expose-headers:
       - X-Request-ID
@@ -1015,4 +1014,153 @@ interactions:
     status:
       code: 200
       message: OK
+- request:
+    body: '{"messages":[{"content":"You are a text manipulation algorithm.","role":"system"},{"content":"Call
+      the add_exclamation_mcp tool with message=\"Hello\". Reply with only the tool
+      output, no other text.","role":"user"}],"model":"gpt-3.5-turbo","stream":false,"temperature":0.7,"tools":[{"type":"function","function":{"name":"add_exclamation_mcp","description":"Adds
+      an exclamation mark to the input message.","parameters":{"properties":{"message":{"type":"string"}},"required":["message"],"type":"object"}}}]}'
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      authorization:
+      - XXXXXX
+      connection:
+      - keep-alive
+      content-type:
+      - application/json
+    method: POST
+    uri: https://api.openai.com/v1/chat/completions
+  response:
+    body:
+      string: '{"id": "chatcmpl-DzVrTIy5YWxOo2JjHyNNLCEoZeIQ5", "object": "chat.completion",
+        "created": 1783552855, "model": "gpt-3.5-turbo-0125", "choices": [{"index":
+        0, "message": {"role": "assistant", "content": null, "tool_calls": [{"id":
+        "call_FI6Wqecvc3Pm1sIJIWbfiPqn", "type": "function", "function": {"name":
+        "add_exclamation_mcp", "arguments": "{\"message\":\"Hello\"}"}}], "refusal":
+        null, "annotations": []}, "logprobs": null, "finish_reason": "tool_calls"}],
+        "usage": {"prompt_tokens": 82, "completion_tokens": 17, "total_tokens": 99,
+        "prompt_tokens_details": {"cached_tokens": 0, "audio_tokens": 0}, "completion_tokens_details":
+        {"reasoning_tokens": 0, "audio_tokens": 0, "accepted_prediction_tokens": 0,
+        "rejected_prediction_tokens": 0}}, "service_tier": "default", "system_fingerprint":
+        null}'
+    headers:
+      access-control-expose-headers:
+      - X-Request-ID
+      - CF-Ray
+      - CF-Ray
+      cf-cache-status:
+      - DYNAMIC
+      cf-ray:
+      - a182d27a8acc5ee6-PDX
+      connection:
+      - keep-alive
+      content-type:
+      - application/json
+      date:
+      - Wed, 08 Jul 2026 23:20:56 GMT
+      openai-organization:
+      - nr-test-org
+      openai-processing-ms:
+      - '1537'
+      openai-project:
+      - nr-test-project
+      openai-version:
+      - '2020-10-01'
+      server:
+      - cloudflare
+      transfer-encoding:
+      - chunked
+      x-ratelimit-limit-requests:
+      - '10000'
+      x-ratelimit-limit-tokens:
+      - '50000000'
+      x-ratelimit-remaining-requests:
+      - '9999'
+      x-ratelimit-remaining-tokens:
+      - '49999975'
+      x-ratelimit-reset-requests:
+      - 6ms
+      x-ratelimit-reset-tokens:
+      - 0s
+      x-request-id:
+      - req_769ac9ab9bce44929dff73538cc803d1
+    status:
+      code: 200
+      message: OK
+- request:
+    body: '{"messages":[{"content":"You are a text manipulation algorithm.","role":"system"},{"content":"Call
+      the add_exclamation_mcp tool with message=\"Hello\". Reply with only the tool
+      output, no other text.","role":"user"},{"content":null,"name":"my_agent","role":"assistant","tool_calls":[{"type":"function","id":"call_FI6Wqecvc3Pm1sIJIWbfiPqn","function":{"name":"add_exclamation_mcp","arguments":"{\"message\":
+      \"Hello\"}"}}]},{"content":[{"type":"text","text":"Hello!"}],"role":"tool","tool_call_id":"call_FI6Wqecvc3Pm1sIJIWbfiPqn"}],"model":"gpt-3.5-turbo","stream":false,"temperature":0.7,"tools":[{"type":"function","function":{"name":"add_exclamation_mcp","description":"Adds
+      an exclamation mark to the input message.","parameters":{"properties":{"message":{"type":"string"}},"required":["message"],"type":"object"}}}]}'
+    headers:
+      accept:
+      - application/json
+      accept-encoding:
+      - gzip, deflate, zstd
+      authorization:
+      - XXXXXX
+      connection:
+      - keep-alive
+      content-type:
+      - application/json
+    method: POST
+    uri: https://api.openai.com/v1/chat/completions
+  response:
+    body:
+      string: '{"id": "chatcmpl-DzVrUApwqEqiJqmsGYi0xyFRiHOG5", "object": "chat.completion",
+        "created": 1783552856, "model": "gpt-3.5-turbo-0125", "choices": [{"index":
+        0, "message": {"role": "assistant", "content": "{\"message\":\"Hello!\"}",
+        "refusal": null, "annotations": []}, "logprobs": null, "finish_reason": "stop"}],
+        "usage": {"prompt_tokens": 115, "completion_tokens": 7, "total_tokens": 122,
+        "prompt_tokens_details": {"cached_tokens": 0, "audio_tokens": 0}, "completion_tokens_details":
+        {"reasoning_tokens": 0, "audio_tokens": 0, "accepted_prediction_tokens": 0,
+        "rejected_prediction_tokens": 0}}, "service_tier": "default", "system_fingerprint":
+        null}'
+    headers:
+      access-control-expose-headers:
+      - X-Request-ID
+      - CF-Ray
+      - CF-Ray
+      cf-cache-status:
+      - DYNAMIC
+      cf-ray:
+      - a182d2894ae25ee6-PDX
+      connection:
+      - keep-alive
+      content-type:
+      - application/json
+      date:
+      - Wed, 08 Jul 2026 23:20:57 GMT
+      openai-organization:
+      - nr-test-org
+      openai-processing-ms:
+      - '409'
+      openai-project:
+      - nr-test-project
+      openai-version:
+      - '2020-10-01'
+      server:
+      - cloudflare
+      transfer-encoding:
+      - chunked
+      x-ratelimit-limit-requests:
+      - '10000'
+      x-ratelimit-limit-tokens:
+      - '50000000'
+      x-ratelimit-remaining-requests:
+      - '9999'
+      x-ratelimit-remaining-tokens:
+      - '49999975'
+      x-ratelimit-reset-requests:
+      - 6ms
+      x-ratelimit-reset-tokens:
+      - 0s
+      x-request-id:
+      - req_3a560a188af14f67890e2b1ad837bd71
+    status:
+      code: 200
+      message: OK
 version: 1

tests/mlmodel_langchain/test_remote_tools.py

@@ -0,0 +1,112 @@
+# Copyright 2010 New Relic, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import pytest
+from langchain.messages import HumanMessage
+from mcp.server.fastmcp import FastMCP
+from mcp.shared.memory import create_connected_server_and_client_session
+from testing_support.fixtures import dt_enabled, reset_core_stats_engine, validate_attributes
+from testing_support.validators.validate_custom_events import validate_custom_events
+from testing_support.validators.validate_span_events import validate_span_events
+from testing_support.validators.validate_transaction_metrics import validate_transaction_metrics
+
+from newrelic.api.background_task import background_task
+from newrelic.hooks.mlmodel_langchain import _is_local_tool
+
+PROMPT = {
+    "messages": [
+        HumanMessage(
+            'Call the add_exclamation_mcp tool with message="Hello". Reply with only the tool output, no other text.'
+        )
+    ]
+}
+
+tool_recorded_event = [
+    (
+        {"type": "LlmTool"},
+        {
+            "id": None,
+            "run_id": None,
+            # MCP adapters return the result as a content block carrying a random uuid, so
+            # the exact output string is non-deterministic. We can only assert the key
+            # is present, not its value.
+            "output": None,
+            "name": "add_exclamation_mcp",
+            "agent_name": "my_agent",
+            "span_id": None,
+            "trace_id": "trace-id",
+            "input": "{'message': 'Hello'}",
+            "vendor": "langchain",
+            "ingest_source": "Python",
+            "duration": None,
+        },
+    )
+]
+
+
+@pytest.fixture
+def mcp_server():
+    server = FastMCP("Test Tools")
+
+    @server.tool()
+    def add_exclamation_mcp(message: str) -> str:
+        """Adds an exclamation mark to the input message."""
+        return f"{message}!"
+
+    return server
+
+
+@dt_enabled
+@reset_core_stats_engine()
+def test_remote_mcp_tool_no_subcomponent(loop, set_trace_info, chat_openai_client, mcp_server):
+    @validate_custom_events(tool_recorded_event)
+    @validate_transaction_metrics(
+        "test_remote_mcp_tool_no_subcomponent",
+        scoped_metrics=[("Llm/tool/LangChain/arun/add_exclamation_mcp", 1)],
+        rollup_metrics=[("Llm/tool/LangChain/arun/add_exclamation_mcp", 1)],
+        background_task=True,
+    )
+    @validate_attributes("agent", ["llm"])
+    # Agent span still has a subcomponent attribute as the agent is executing locally
+    @validate_span_events(count=1, exact_agents={"subcomponent": '{"type": "APM-AI_AGENT", "name": "my_agent"}'})
+    # Tool span must NOT have a subcomponent attribute as it will be captured on the server side
+    @validate_span_events(
+        count=1,
+        exact_intrinsics={"name": "Llm/tool/LangChain/arun/add_exclamation_mcp"},
+        unexpected_agents=["subcomponent"],
+    )
+    @background_task(name="test_remote_mcp_tool_no_subcomponent")
+    def _test():
+        set_trace_info()
+
+        async def _run():
+            from langchain.agents import create_agent
+            from langchain_mcp_adapters.tools import load_mcp_tools
+
+            async with create_connected_server_and_client_session(mcp_server) as session:
+                tools = await load_mcp_tools(session)
+                # The loaded tool is a genuine remote proxy, so the fix must treat it as non-local.
+                assert _is_local_tool(tools[0]) is False
+
+                agent = create_agent(
+                    model=chat_openai_client.with_config(model="gpt-5.1", timeout=30),
+                    tools=tools,
+                    system_prompt="You are a text manipulation algorithm.",
+                    name="my_agent",
+                )
+                return await agent.ainvoke(PROMPT)
+
+        loop.run_until_complete(_run())
+
+    _test()

tox.ini

@@ -477,6 +477,7 @@ deps =
     mlmodel_langchain: langchain-openai
     mlmodel_langchain: pytest-recording
     mlmodel_langchain: langgraph
+    mlmodel_langchain: langchain-mcp-adapters
     mlmodel_langchain: pypdf
     mlmodel_langchain: tiktoken
     mlmodel_langchain: faiss-cpu