fix: handle MCP list tools spans with GenAI semantics

- Add GenAIOperationName.LIST_TOOLS constant
- Implement _get_attributes_from_mcp_list_tools_span_data to extract operation name, tool definitions, and output type
- Update _extract_genai_attributes dispatch for MCPListToolsSpanData
- Add test coverage for MCP list tools attribute extraction
- Update CHANGELOG

Fixes #4197

Author: Ayush-Gupta100

instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/CHANGELOG.md

@@ -7,19 +7,14 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## Unreleased
 
-### Added
-
 - Align AgentSpanData test stubs and span processor with real OpenAI Agents SDK;
   remove non-existent `operation`, `description`, `agent_id`, and `model` fields.
   ([#4229](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4229))
 - Document official package metadata and README for the OpenAI Agents instrumentation.
   ([#3859](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/3859))
 - Populate instructions and tool definitions from Response obj.
   ([#4196](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4196))
-
-### Fixed
-
-- `opentelemetry-instrumentation-openai-agents`: Handle MCP list tools spans correctly.
+- `opentelemetry-instrumentation-openai-agents-v2`: Handle MCP list tools spans correctly.
   ([#4508](https://github.com/open-telemetry/opentelemetry-python-contrib/pull/4508))
 
 ## Version 0.1.0 (2025-10-15)

instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/src/opentelemetry/instrumentation/openai_agents/span_processor.py

@@ -122,6 +122,7 @@ class GenAIOperationName:
     SPEECH = "speech_generation"
     GUARDRAIL = "guardrail_check"
     HANDOFF = "agent_handoff"
+    LIST_TOOLS = "list_tools"
     RESPONSE = "response"  # internal aggregator in current processor
 
     CLASS_FALLBACK = {
@@ -1159,6 +1160,8 @@ def _infer_output_type(self, span_data: Any) -> str:
         if _is_instance_of(span_data, FunctionSpanData):
             # Tool results are typically JSON
             return GenAIOutputType.JSON
+        if _is_instance_of(span_data, MCPListToolsSpanData):
+            return GenAIOutputType.JSON
         if _is_instance_of(span_data, TranscriptionSpanData):
             return GenAIOutputType.TEXT
         if _is_instance_of(span_data, SpeechSpanData):
@@ -1548,7 +1551,7 @@ def _get_operation_name(self, span_data: Any) -> str:
         if _is_instance_of(span_data, HandoffSpanData):
             return GenAIOperationName.HANDOFF
         if _is_instance_of(span_data, MCPListToolsSpanData):
-            return "list_tools"
+            return GenAIOperationName.LIST_TOOLS
         return "unknown"
 
     def _extract_genai_attributes(
@@ -1609,6 +1612,10 @@ def _extract_genai_attributes(
             yield from self._get_attributes_from_guardrail_span_data(span_data)
         elif _is_instance_of(span_data, HandoffSpanData):
             yield from self._get_attributes_from_handoff_span_data(span_data)
+        elif _is_instance_of(span_data, MCPListToolsSpanData):
+            yield from self._get_attributes_from_mcp_list_tools_span_data(
+                span_data
+            )
 
     def _get_attributes_from_generation_span_data(
         self, span_data: GenerationSpanData, payload: ContentPayload
@@ -2174,6 +2181,21 @@ def _get_attributes_from_handoff_span_data(
             normalize_output_type(self._infer_output_type(span_data)),
         )
 
+    def _get_attributes_from_mcp_list_tools_span_data(
+        self, span_data: MCPListToolsSpanData
+    ) -> Iterator[tuple[str, AttributeValue]]:
+        """Extract attributes from MCP list-tools spans."""
+        yield GEN_AI_OPERATION_NAME, GenAIOperationName.LIST_TOOLS
+
+        tools = getattr(span_data, "tools", None)
+        if self._capture_tool_definitions and tools:
+            yield GEN_AI_TOOL_DEFINITIONS, safe_json_dumps(tools)
+
+        yield (
+            GEN_AI_OUTPUT_TYPE,
+            normalize_output_type(self._infer_output_type(span_data)),
+        )
+
     def _cleanup_spans_for_trace(self, trace_id: str) -> None:
         """Clean up spans for a trace to prevent memory leaks."""
         spans_to_remove = [

instrumentation-genai/opentelemetry-instrumentation-openai-agents-v2/tests/test_z_span_processor_unit.py

@@ -183,7 +183,10 @@ def test_operation_and_span_naming(processor_setup):
     )
 
     mcp_data = MCPListToolsSpanData()
-    assert processor._get_operation_name(mcp_data) == "list_tools"
+    assert (
+        processor._get_operation_name(mcp_data)
+        == sp.GenAIOperationName.LIST_TOOLS
+    )
 
     class UnknownSpanData:
         pass
@@ -362,6 +365,21 @@ def __init__(self) -> None:
     assert function_attrs[sp.GEN_AI_TOOL_CALL_RESULT] == {"temperature": 70}
     assert function_attrs[sp.GEN_AI_OUTPUT_TYPE] == sp.GenAIOutputType.JSON
 
+    mcp_span = MCPListToolsSpanData(
+        tools=[{"type": "function", "name": "lookup_weather"}]
+    )
+    mcp_attrs = _collect(
+        processor._get_attributes_from_mcp_list_tools_span_data(mcp_span)
+    )
+    assert (
+        mcp_attrs[sp.GEN_AI_OPERATION_NAME]
+        == sp.GenAIOperationName.LIST_TOOLS
+    )
+    assert json.loads(mcp_attrs[sp.GEN_AI_TOOL_DEFINITIONS]) == [
+        {"type": "function", "name": "lookup_weather"}
+    ]
+    assert mcp_attrs[sp.GEN_AI_OUTPUT_TYPE] == sp.GenAIOutputType.JSON
+
 
 def test_extract_genai_attributes_unknown_type(processor_setup):
     processor, _ = processor_setup