Reapply span attributes after creation to survive non-forwarding samplers

Tracer.start_span builds the span from sampling_result.attributes, not
the attributes kwarg — a custom Sampler that returns
SamplingResult(RECORD_AND_SAMPLE) without forwarding attributes
silently drops everything FastMCP passed at creation time. Reapply the
same attributes immediately after span creation (guarded by
is_recording()) so on_start hooks and samplers still see them, while
the finished span is guaranteed to carry FastMCP's telemetry
regardless of sampler behavior.

fastmcp_slim/fastmcp/client/telemetry.py

@@ -23,9 +23,6 @@ def client_span(
 
     Automatically records any exception on the span and sets error status.
     """
-    tracer = get_tracer()
-    with tracer.start_as_current_span(name, kind=SpanKind.CLIENT) as span:
-        if span.is_recording():
     attrs: dict[str, str] = {
         # MCP semantic conventions
         "mcp.method.name": method,
@@ -40,6 +37,20 @@ def client_span(
         attrs["gen_ai.tool.name"] = tool_name
     if prompt_name is not None:
         attrs["gen_ai.prompt.name"] = prompt_name
+
+    tracer = get_tracer()
+    with tracer.start_as_current_span(
+        name, kind=SpanKind.CLIENT, attributes=attrs
+    ) as span:
+        # Reapply: `attributes=attrs` above lets on_start hooks and the
+        # sampler see these values at creation time. But OTel's
+        # Tracer.start_span builds the span from
+        # `sampling_result.attributes`, not the `attributes` kwarg directly —
+        # a custom Sampler whose SamplingResult.attributes defaults to None
+        # silently drops everything we passed. Reapplying here (additive,
+        # can't clobber anything a sampler legitimately added) guarantees
+        # FastMCP's attributes survive regardless of sampler behavior.
+        if span.is_recording():
             span.set_attributes(attrs)
         try:
             yield span

fastmcp_slim/fastmcp/server/sampling/run.py

@@ -310,13 +310,26 @@ async def execute_tools(
             )
 
         tracer = get_tracer()
+        span_attrs = {
+            "gen_ai.tool.name": tool_use.name,
+            "fastmcp.tool.use_id": tool_use.id,
+        }
         with tracer.start_as_current_span(
             f"sampling tool {tool_use.name}",
             kind=SpanKind.INTERNAL,
+            attributes=span_attrs,
         ) as span:
+            # Reapply: `attributes=span_attrs` above lets on_start hooks and
+            # the sampler see these values at creation time. But OTel's
+            # Tracer.start_span builds the span from
+            # `sampling_result.attributes`, not the `attributes` kwarg
+            # directly — a custom Sampler whose SamplingResult.attributes
+            # defaults to None silently drops everything we passed.
+            # Reapplying here (additive, can't clobber anything a sampler
+            # legitimately added) guarantees FastMCP's attributes survive
+            # regardless of sampler behavior.
             if span.is_recording():
-                span.set_attribute("gen_ai.tool.name", tool_use.name)
-                span.set_attribute("fastmcp.tool.use_id", tool_use.id)
+                span.set_attributes(span_attrs)
             try:
                 result_value = await tool.run(tool_use.input)
                 return ToolResultContent(
@@ -553,15 +566,27 @@ async def sample_step_impl(
 
     # Make the LLM call
     tracer = get_tracer()
+    span_attrs = {
+        "mcp.method.name": "sampling/createMessage",
+        "fastmcp.server.name": context.fastmcp.name,
+    }
     with tracer.start_as_current_span(
         "sampling create_message",
         kind=SpanKind.CLIENT,
+        attributes=span_attrs,
         record_exception=False,
         set_status_on_exception=False,
     ) as span:
+        # Reapply: `attributes=span_attrs` above lets on_start hooks and the
+        # sampler see these values at creation time. But OTel's
+        # Tracer.start_span builds the span from
+        # `sampling_result.attributes`, not the `attributes` kwarg directly —
+        # a custom Sampler whose SamplingResult.attributes defaults to None
+        # silently drops everything we passed. Reapplying here (additive,
+        # can't clobber anything a sampler legitimately added) guarantees
+        # FastMCP's attributes survive regardless of sampler behavior.
         if span.is_recording():
-            span.set_attribute("mcp.method.name", "sampling/createMessage")
-            span.set_attribute("fastmcp.server.name", context.fastmcp.name)
+            span.set_attributes(span_attrs)
         try:
             if use_fallback:
                 response = await call_sampling_handler(

fastmcp_slim/fastmcp/server/telemetry.py

@@ -135,23 +135,31 @@ def seam_span(method: str, server_name: str) -> Generator[Span, None, None]:
     rejections *before* the high-level path (auth, not-found, middleware vetoes)
     that would otherwise produce no SERVER span at all — are recorded here.
     """
-    tracer = get_tracer()
-    with tracer.start_as_current_span(
-        method,
-        context=_get_parent_trace_context(),
-        kind=SpanKind.SERVER,
-    ) as span:
-        if span.is_recording():
-            span.set_attribute(SEAM_SPAN_MARKER, True)
-            span.set_attributes(
-                {
+    attrs = {
+        SEAM_SPAN_MARKER: True,
         "mcp.method.name": method,
         "fastmcp.server.name": server_name,
         **get_protocol_span_attributes(),
         **get_auth_span_attributes(),
         **get_session_span_attributes(),
     }
-            )
+    tracer = get_tracer()
+    with tracer.start_as_current_span(
+        method,
+        context=_get_parent_trace_context(),
+        kind=SpanKind.SERVER,
+        attributes=attrs,
+    ) as span:
+        # Reapply: `attributes=attrs` above is what makes on_start hooks and
+        # the sampler see these values at creation time (the whole point of
+        # this helper). But OTel's Tracer.start_span builds the span from
+        # `sampling_result.attributes`, not the `attributes` kwarg directly —
+        # a custom Sampler whose SamplingResult.attributes defaults to None
+        # silently drops everything we passed. Reapplying here (additive,
+        # can't clobber anything a sampler legitimately added) guarantees
+        # FastMCP's attributes survive regardless of sampler behavior.
+        if span.is_recording():
+            span.set_attributes(attrs)
         token = _active_seam_span.set(span)
         try:
             yield span
@@ -218,7 +226,11 @@ def server_span(
         name,
         context=_get_parent_trace_context(),
         kind=SpanKind.SERVER,
+        attributes=attrs,
     ) as span:
+        # Reapply for the same reason as `seam_span`: OTel builds the span
+        # from `sampling_result.attributes`, which a custom Sampler may not
+        # forward even though it was handed `attributes=attrs` above.
         if span.is_recording():
             span.set_attributes(attrs)
         try:
@@ -240,15 +252,19 @@ def delegate_span(
     Used by FastMCPProvider when delegating to mounted servers.
     Automatically records any exception on the span and sets error status.
     """
-    tracer = get_tracer()
-    with tracer.start_as_current_span(f"delegate {name}") as span:
-        if span.is_recording():
     attrs: dict[str, str] = {
         "fastmcp.provider.type": provider_type,
         "fastmcp.component.key": component_key,
     }
     if method is not None:
         attrs["mcp.method.name"] = method
+
+    tracer = get_tracer()
+    with tracer.start_as_current_span(f"delegate {name}", attributes=attrs) as span:
+        # Reapply for the same reason as `seam_span`: OTel builds the span
+        # from `sampling_result.attributes`, which a custom Sampler may not
+        # forward even though it was handed `attributes=attrs` above.
+        if span.is_recording():
             span.set_attributes(attrs)
         try:
             yield span

tests/server/telemetry/test_sampling_tracing.py

@@ -10,13 +10,66 @@ from __future__ import annotations
 
 import pytest
 from mcp_types import TextContent
+from opentelemetry.context import Context as OTelContext
+from opentelemetry.sdk.trace import Span, SpanProcessor, TracerProvider
+from opentelemetry.sdk.trace.export import SimpleSpanProcessor
 from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter
+from opentelemetry.sdk.trace.sampling import Decision, Sampler, SamplingResult
 from opentelemetry.trace import StatusCode
 
 from fastmcp import Client, Context, FastMCP
 from fastmcp.client.sampling import RequestContext, SamplingMessage, SamplingParams
 
 
+class OnStartRecorder(SpanProcessor):
+    def __init__(self) -> None:
+        self.attributes: dict[str, dict[str, object]] = {}
+
+    def on_start(self, span: Span, parent_context: OTelContext | None = None) -> None:
+        self.attributes[span.name] = dict(span.attributes or {})
+
+
+class NonForwardingSampler(Sampler):
+    """Samples every span but never forwards the attributes it was handed.
+
+    See `tests/telemetry/test_span_attributes.py` for the full explanation:
+    OTel's `Tracer.start_span` builds the finished span from
+    `sampling_result.attributes`, not from the `attributes` kwarg passed to
+    `start_as_current_span`, so a custom sampler like this one reproduces the
+    regression where a non-forwarding sampler silently drops FastMCP's
+    attributes.
+    """
+
+    def should_sample(
+        self,
+        parent_context: OTelContext | None,
+        trace_id: int,
+        name: str,
+        kind: object = None,
+        attributes: object = None,
+        links: object = None,
+        trace_state: object = None,
+    ) -> SamplingResult:
+        return SamplingResult(Decision.RECORD_AND_SAMPLE)
+
+    def get_description(self) -> str:
+        return "NonForwardingSampler"
+
+
+@pytest.fixture
+def on_start_recorder(
+    monkeypatch: pytest.MonkeyPatch,
+    trace_exporter: InMemorySpanExporter,
+) -> OnStartRecorder:
+    recorder = OnStartRecorder()
+    provider = TracerProvider()
+    provider.add_span_processor(recorder)
+    provider.add_span_processor(SimpleSpanProcessor(trace_exporter))
+    tracer = provider.get_tracer("test")
+    monkeypatch.setattr("fastmcp.server.sampling.run.get_tracer", lambda: tracer)
+    return recorder
+
+
 def _spans_named(exporter: InMemorySpanExporter, name: str):
     return [s for s in exporter.get_finished_spans() if s.name == name]
 
@@ -27,7 +80,9 @@ def _exception_events(span):
 
 class TestSamplingCreateMessageSpan:
     async def test_success_creates_span_with_attributes(
-        self, trace_exporter: InMemorySpanExporter
+        self,
+        trace_exporter: InMemorySpanExporter,
+        on_start_recorder: OnStartRecorder,
     ):
         def sampling_handler(
             messages: list[SamplingMessage],
@@ -52,6 +107,10 @@ class TestSamplingCreateMessageSpan:
         assert span.attributes is not None
         assert span.attributes["mcp.method.name"] == "sampling/createMessage"
         assert span.attributes["fastmcp.server.name"] == "sampling-server"
+        assert on_start_recorder.attributes["sampling create_message"] == {
+            "mcp.method.name": "sampling/createMessage",
+            "fastmcp.server.name": "sampling-server",
+        }
         # Success path must not record any exception.
         assert _exception_events(span) == []
         assert span.status.status_code != StatusCode.ERROR
@@ -93,7 +152,9 @@ class TestSamplingCreateMessageSpan:
 
 class TestSamplingToolSpan:
     async def test_tool_error_span_records_exception_once(
-        self, trace_exporter: InMemorySpanExporter
+        self,
+        trace_exporter: InMemorySpanExporter,
+        on_start_recorder: OnStartRecorder,
     ):
         from mcp_types import CreateMessageResultWithTools, ToolUseContent
 
@@ -146,7 +207,124 @@ class TestSamplingToolSpan:
         assert span.status.status_code == StatusCode.ERROR
         assert span.attributes is not None
         assert span.attributes["gen_ai.tool.name"] == "boom_tool"
+        assert on_start_recorder.attributes["sampling tool boom_tool"] == {
+            "gen_ai.tool.name": "boom_tool",
+            "fastmcp.tool.use_id": "call_1",
+        }
         assert "error.type" in span.attributes
         # Tool spans catch-and-convert (no re-raise), so OTel auto-recording
         # never fires; the manual record_exception must fire exactly once.
         assert len(_exception_events(span)) == 1
+
+
+class TestAttributesSurviveANonForwardingSampler:
+    """Regression: `sampling create_message` and `sampling tool ...` spans
+    must keep FastMCP's attributes even when the configured Sampler doesn't
+    forward the `attributes` it was handed to its `SamplingResult`.
+    """
+
+    @pytest.fixture
+    def non_forwarding_recorder(
+        self,
+        monkeypatch: pytest.MonkeyPatch,
+        trace_exporter: InMemorySpanExporter,
+    ) -> OnStartRecorder:
+        recorder = OnStartRecorder()
+        provider = TracerProvider(sampler=NonForwardingSampler())
+        provider.add_span_processor(recorder)
+        provider.add_span_processor(SimpleSpanProcessor(trace_exporter))
+        tracer = provider.get_tracer("test")
+        monkeypatch.setattr("fastmcp.server.sampling.run.get_tracer", lambda: tracer)
+        return recorder
+
+    async def test_create_message_span_keeps_attributes(
+        self,
+        trace_exporter: InMemorySpanExporter,
+        non_forwarding_recorder: OnStartRecorder,
+    ):
+        def sampling_handler(
+            messages: list[SamplingMessage],
+            params: SamplingParams,
+            ctx: RequestContext,
+        ) -> str:
+            return "sampled-text"
+
+        mcp = FastMCP("sampling-server")
+
+        @mcp.tool
+        async def ask(question: str, context: Context) -> str:
+            result = await context.sample(messages=question)
+            return result.text or ""
+
+        async with Client(mcp, sampling_handler=sampling_handler) as client:
+            await client.call_tool("ask", {"question": "hi"})
+
+        spans = _spans_named(trace_exporter, "sampling create_message")
+        assert len(spans) == 1
+        span = spans[0]
+        assert span.attributes is not None
+        assert span.attributes["mcp.method.name"] == "sampling/createMessage"
+        assert span.attributes["fastmcp.server.name"] == "sampling-server"
+        # The sampler never forwards attributes, so on_start legitimately sees
+        # none — this documents that limitation rather than asserting around it.
+        assert non_forwarding_recorder.attributes["sampling create_message"] == {}
+
+    async def test_sampling_tool_span_keeps_attributes(
+        self,
+        trace_exporter: InMemorySpanExporter,
+        non_forwarding_recorder: OnStartRecorder,
+    ):
+        from mcp_types import CreateMessageResultWithTools, ToolUseContent
+
+        def echo_tool(text: str) -> str:
+            return text
+
+        call_count = 0
+
+        def sampling_handler(
+            messages: list[SamplingMessage],
+            params: SamplingParams,
+            ctx: RequestContext,
+        ) -> CreateMessageResultWithTools:
+            nonlocal call_count
+            call_count += 1
+            if call_count == 1:
+                return CreateMessageResultWithTools(
+                    role="assistant",
+                    content=[
+                        ToolUseContent(
+                            type="tool_use",
+                            id="call_1",
+                            name="echo_tool",
+                            input={"text": "hi"},
+                        )
+                    ],
+                    model="test-model",
+                    stop_reason="toolUse",
+                )
+            return CreateMessageResultWithTools(
+                role="assistant",
+                content=[TextContent(type="text", text="done")],
+                model="test-model",
+                stop_reason="endTurn",
+            )
+
+        mcp = FastMCP(sampling_handler=sampling_handler)
+
+        @mcp.tool
+        async def driver(context: Context) -> str:
+            result = await context.sample(messages="go", tools=[echo_tool])
+            return result.text or ""
+
+        async with Client(mcp) as client:
+            await client.call_tool("driver", {})
+
+        spans = _spans_named(trace_exporter, "sampling tool echo_tool")
+        assert len(spans) == 1
+        span = spans[0]
+        assert span.attributes is not None
+        assert span.attributes["gen_ai.tool.name"] == "echo_tool"
+        assert span.attributes["fastmcp.tool.use_id"] == "call_1"
+        # The sampler never forwards attributes, so on_start legitimately sees
+        # none — this documents that limitation rather than asserting around it.
+        assert non_forwarding_recorder.attributes["sampling tool echo_tool"] == {}

tests/telemetry/test_span_attributes.py

@@ -0,0 +1,205 @@
+from collections.abc import Callable
+from contextlib import AbstractContextManager
+
+import pytest
+from opentelemetry.context import Context
+from opentelemetry.sdk.trace import Span, SpanProcessor, TracerProvider
+from opentelemetry.sdk.trace.export import SimpleSpanProcessor
+from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter
+from opentelemetry.sdk.trace.sampling import Decision, Sampler, SamplingResult
+from opentelemetry.trace import Span as APISpan
+
+from fastmcp.client.telemetry import client_span
+from fastmcp.server.telemetry import delegate_span, seam_span, server_span
+
+
+class OnStartRecorder(SpanProcessor):
+    def __init__(self) -> None:
+        self.attributes: dict[str, dict[str, object]] = {}
+
+    def on_start(self, span: Span, parent_context: Context | None = None) -> None:
+        self.attributes[span.name] = dict(span.attributes or {})
+
+
+class NonForwardingSampler(Sampler):
+    """Samples every span but never forwards the attributes it was handed.
+
+    Mirrors a real-world custom sampler that builds its own `SamplingResult`
+    without threading through the `attributes` it received — the
+    `attributes` parameter defaults to `None`, so `RECORD_AND_SAMPLE` with no
+    `attributes` argument reproduces the regression: OTel's `Tracer.start_span`
+    constructs the span from `sampling_result.attributes`, not from the
+    `attributes` kwarg passed to `start_as_current_span`.
+    """
+
+    def should_sample(
+        self,
+        parent_context: Context | None,
+        trace_id: int,
+        name: str,
+        kind: object = None,
+        attributes: object = None,
+        links: object = None,
+        trace_state: object = None,
+    ) -> SamplingResult:
+        return SamplingResult(Decision.RECORD_AND_SAMPLE)
+
+    def get_description(self) -> str:
+        return "NonForwardingSampler"
+
+
+def test_known_span_attributes_are_available_on_start(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    recorder = OnStartRecorder()
+    provider = TracerProvider()
+    provider.add_span_processor(recorder)
+    tracer = provider.get_tracer("test")
+    monkeypatch.setattr("fastmcp.client.telemetry.get_tracer", lambda: tracer)
+    monkeypatch.setattr("fastmcp.server.telemetry.get_tracer", lambda: tracer)
+
+    with client_span(
+        "client test",
+        method="tools/call",
+        component_key="tool:echo@",
+        tool_name="echo",
+    ):
+        pass
+    with server_span(
+        "server test",
+        method="tools/call",
+        server_name="test-server",
+        component_type="tool",
+        component_key="tool:echo@",
+        tool_name="echo",
+    ):
+        pass
+    with seam_span("initialize test", server_name="test-server"):
+        pass
+    with delegate_span(
+        "delegate test",
+        provider_type="LocalProvider",
+        component_key="tool:echo@",
+        method="tools/call",
+    ):
+        pass
+
+    assert recorder.attributes["client test"] == {
+        "mcp.method.name": "tools/call",
+        "fastmcp.component.key": "tool:echo@",
+        "gen_ai.tool.name": "echo",
+    }
+    assert recorder.attributes["server test"] == {
+        "mcp.method.name": "tools/call",
+        "fastmcp.server.name": "test-server",
+        "fastmcp.component.type": "tool",
+        "fastmcp.component.key": "tool:echo@",
+        "gen_ai.tool.name": "echo",
+    }
+    assert recorder.attributes["initialize test"] == {
+        "fastmcp.span.seam": True,
+        "mcp.method.name": "initialize test",
+        "fastmcp.server.name": "test-server",
+    }
+    assert recorder.attributes["delegate delegate test"] == {
+        "fastmcp.provider.type": "LocalProvider",
+        "fastmcp.component.key": "tool:echo@",
+        "mcp.method.name": "tools/call",
+    }
+
+
+SPAN_HELPER_CASES = [
+    pytest.param(
+        lambda: client_span(
+            "client test",
+            method="tools/call",
+            component_key="tool:echo@",
+            tool_name="echo",
+        ),
+        "client test",
+        {
+            "mcp.method.name": "tools/call",
+            "fastmcp.component.key": "tool:echo@",
+            "gen_ai.tool.name": "echo",
+        },
+        id="client_span",
+    ),
+    pytest.param(
+        lambda: server_span(
+            "server test",
+            method="tools/call",
+            server_name="test-server",
+            component_type="tool",
+            component_key="tool:echo@",
+            tool_name="echo",
+        ),
+        "server test",
+        {
+            "mcp.method.name": "tools/call",
+            "fastmcp.server.name": "test-server",
+            "fastmcp.component.type": "tool",
+            "fastmcp.component.key": "tool:echo@",
+            "gen_ai.tool.name": "echo",
+        },
+        id="server_span",
+    ),
+    pytest.param(
+        lambda: seam_span("initialize test", server_name="test-server"),
+        "initialize test",
+        {
+            "fastmcp.span.seam": True,
+            "mcp.method.name": "initialize test",
+            "fastmcp.server.name": "test-server",
+        },
+        id="seam_span",
+    ),
+    pytest.param(
+        lambda: delegate_span(
+            "delegate test",
+            provider_type="LocalProvider",
+            component_key="tool:echo@",
+            method="tools/call",
+        ),
+        "delegate delegate test",
+        {
+            "fastmcp.provider.type": "LocalProvider",
+            "fastmcp.component.key": "tool:echo@",
+            "mcp.method.name": "tools/call",
+        },
+        id="delegate_span",
+    ),
+]
+
+
+@pytest.mark.parametrize(
+    ("span_factory", "span_name", "expected_attrs"), SPAN_HELPER_CASES
+)
+def test_attributes_survive_a_non_forwarding_sampler(
+    monkeypatch: pytest.MonkeyPatch,
+    span_factory: Callable[[], AbstractContextManager[APISpan]],
+    span_name: str,
+    expected_attrs: dict[str, object],
+) -> None:
+    """Regression: a custom Sampler that samples a span but doesn't forward
+    the `attributes` it was handed must not erase FastMCP's telemetry.
+
+    OTel's `Tracer.start_span` builds the finished span from
+    `sampling_result.attributes`, not from the `attributes` kwarg passed to
+    `start_as_current_span`. Built-in samplers forward what they're given, but
+    a custom sampler can legally return `SamplingResult(attributes=None)` and
+    silently drop everything FastMCP passed in. The span helpers must reapply
+    their attributes after span creation so this can't happen.
+    """
+    exporter = InMemorySpanExporter()
+    provider = TracerProvider(sampler=NonForwardingSampler())
+    provider.add_span_processor(SimpleSpanProcessor(exporter))
+    tracer = provider.get_tracer("test")
+    monkeypatch.setattr("fastmcp.client.telemetry.get_tracer", lambda: tracer)
+    monkeypatch.setattr("fastmcp.server.telemetry.get_tracer", lambda: tracer)
+
+    with span_factory():
+        pass
+
+    spans = [s for s in exporter.get_finished_spans() if s.name == span_name]
+    assert len(spans) == 1
+    assert dict(spans[0].attributes or {}) == expected_attrs