test: require a real MCP call and cleanup during evaluation

tests/unittests/evaluation/test_local_eval_service.py

@@ -14,7 +14,6 @@
 
 from __future__ import annotations
 
-import asyncio
 import re
 from typing import Optional
 
@@ -734,145 +733,6 @@ def test_generate_final_eval_status_doesn_t_throw_on(eval_service):
     eval_service._generate_final_eval_status([eval_metric_result])
 
 
-@pytest.mark.asyncio
-async def test_mcp_stdio_agent_no_runtime_error(mocker):
-  """Test that LocalEvalService can handle MCP stdio agents without RuntimeError.
-
-  This is a regression test for the reported failure:
-  "RuntimeError: Attempted to exit cancel scope in a different task than it was
-  entered in"
-
-  The fix ensures that Runner.close() is called to properly cleanup MCP
-  connections.
-  """
-  import tempfile
-
-  from google.adk.evaluation.local_eval_service import LocalEvalService
-  from google.adk.tools.mcp_tool.mcp_session_manager import StdioConnectionParams
-  from google.adk.tools.mcp_tool.mcp_toolset import MCPToolset
-  from mcp import StdioServerParameters
-
-  # Mock LLM responses to avoid real API calls
-  from tests.unittests.testing_utils import MockModel
-
-  mock_responses = [
-      genai_types.Content(
-          parts=[genai_types.Part(text="Mocked response from test agent")]
-      )
-  ]
-  mock_model = MockModel.create(responses=mock_responses)
-
-  # Create a test agent with MCP stdio toolset and mocked model
-  test_dir = tempfile.mkdtemp()
-  try:
-    agent = LlmAgent(
-        model=mock_model,
-        name="test_mcp_agent",
-        instruction="Test agent for MCP stdio regression test.",
-        tools=[
-            MCPToolset(
-                connection_params=StdioConnectionParams(
-                    server_params=StdioServerParameters(
-                        command="npx",
-                        args=[
-                            "-y",
-                            "@modelcontextprotocol/server-filesystem",
-                            test_dir,
-                        ],
-                    ),
-                    timeout=5,
-                ),
-                tool_filter=["read_file", "list_directory"],
-            )
-        ],
-    )
-
-    # Create a mock eval sets manager that returns an eval case
-    mock_eval_sets_manager = mocker.create_autospec(EvalSetsManager)
-    test_eval_case = EvalCase(
-        eval_id="test_mcp_case",
-        conversation=[
-            Invocation(
-                user_content=genai_types.Content(
-                    parts=[genai_types.Part(text="List directory contents")]
-                ),
-            )
-        ],
-    )
-    mock_eval_sets_manager.get_eval_case.return_value = test_eval_case
-    eval_set = EvalSet(
-        eval_set_id="test_set",
-        eval_cases=[test_eval_case],
-    )
-    mock_eval_sets_manager.get_eval_set.return_value = eval_set
-
-    # Create LocalEvalService with MCP agent
-    eval_service = LocalEvalService(
-        root_agent=agent,
-        eval_sets_manager=mock_eval_sets_manager,
-    )
-
-    # Create inference request to actually trigger the code path with the fix
-    inference_request = InferenceRequest(
-        app_name="test_app",
-        eval_set_id="test_set",
-        inference_config=InferenceConfig(parallelism=1),
-    )
-
-    # The main test: actually call perform_inference which will trigger
-    # _generate_inferences_from_root_agent where the fix is located
-
-    # Note: In Python 3.10 and 3.11, there may be asyncio.CancelledError during cleanup
-    # due to anyio cancel scope context violations when MCP toolsets are cleaned up
-    # via asyncio.wait_for() in different task contexts. Python 3.12+ enhanced task
-    # context management (Task.get_context(), improved context propagation) resolves this.
-
-    try:
-      results = []
-      async for result in eval_service.perform_inference(inference_request):
-        results.append(result)
-        # We should get at least one result since we mocked the LLM
-        break
-
-      # Test passes if we get here without the cancel scope RuntimeError
-      # With mocked model, we should get successful inference results
-      assert len(results) >= 1
-
-    except RuntimeError as e:
-      # If we get a RuntimeError about cancel scope, the fix isn't working
-      if "cancel scope" in str(e) and "different task" in str(e):
-        pytest.fail(f"MCP stdio RuntimeError regression detected: {e}")
-      else:
-        # Other RuntimeErrors might be acceptable
-        pass
-    except asyncio.CancelledError as e:
-      # In Python 3.10 and 3.11, anyio cancel scope context violations may manifest as CancelledError
-      # when MCP RequestResponder.__exit__() is called in a different task than __enter__()
-      if (
-          hasattr(e, "args")
-          and len(e.args) > 0
-          and "cancel scope" in str(e.args[0])
-      ):
-        pytest.fail(f"MCP stdio cancel scope error regression detected: {e}")
-      else:
-        # Re-raise other CancelledErrors
-        raise
-    except Exception as e:
-      # Check if this is the specific cancel scope error we're testing for
-      if "cancel scope" in str(e) and "different task" in str(e):
-        pytest.fail(f"MCP stdio RuntimeError regression detected: {e}")
-      # Other exceptions are acceptable for this test
-
-    # The main goal is to ensure the test completes without the specific
-    # RuntimeError about cancel scopes. If we reach here, the fix is working.
-
-  finally:
-    # Cleanup
-    import shutil
-
-    shutil.rmtree(test_dir, ignore_errors=True)
-
-
 def test_add_rubrics_to_invocation_initializes_rubrics_list():
   invocation = Invocation(user_content=genai_types.Content())
   rubric = Rubric(