Summary
Anthropic's MCP connector feature (tools=[{"type": "mcp_toolset", ...}] on client.messages.create(), gated by the mcp-client-2025-11-20 beta header) returns mcp_tool_use and mcp_tool_result content blocks when Claude calls a remote MCP server's tools. The repo's Anthropic tracing does not recognize mcp_tool_use as a tool call at all, so:
- MCP tool calls are never captured into a span (no input, no tool name, no call metadata).
- MCP tool results are still detected (because the result-type check is suffix-based) but are logged as orphaned spans with no call context, since the corresponding call was never registered.
This is a correctness gap, not just missing-coverage: half of each MCP tool exchange is dropped and the other half is logged incompletely/incorrectly.
What is missing
In py/src/braintrust/integrations/anthropic/tracing.py:
_SERVER_TOOL_USE_TYPE = "server_tool_use" # line 1337
def _is_server_tool_result_type(item_type: Any) -> bool: # line 1340
return isinstance(item_type, str) and item_type.endswith("_tool_result") and item_type != "tool_result"
_log_server_tool_spans (line 1455) pairs calls and results by walking response content:
item_type = item.get("type")
if item_type == _SERVER_TOOL_USE_TYPE: # line 1470 — only matches "server_tool_use"
...
continue
if not _is_server_tool_result_type(item_type): # line 1481
continue
- The call-side check only matches the literal string
"server_tool_use" (used for built-in server tools like web search / code execution). It does not match "mcp_tool_use", so mcp_tool_use blocks fall through the loop entirely and are never added to calls_by_id.
- The result-side check (
_is_server_tool_result_type) matches anything ending in _tool_result except the literal tool_result, so mcp_tool_result does pass this check — but since no matching call was ever registered, it's appended as (None, item), producing a tool span with output only and no input/tool name.
Separately, _MANAGED_AGENTS_CALL_TYPES (line 905) does include "agent.mcp_tool_use" — but that's the distinct, agent.-prefixed type used by the Managed Agents API (client.beta.agents/client.beta.sessions), not the plain mcp_tool_use/mcp_tool_result types returned by the standard Messages API's MCP connector.
Braintrust docs status: unclear / not_found
The Anthropic integration page mentions mcp_servers exactly once, as one of many request parameters captured in span metadata for the Go SDK's request-param list. It does not mention mcp_toolset, mcp_tool_use, or mcp_tool_result anywhere, and does not document any tool-span behavior specific to the MCP connector for any language. The only documented span-splitting for server-side tools is generic ("server-side tool calls ... appear as child tool spans"), described for the Java SDK, and is not confirmed to apply to MCP connector blocks specifically.
Upstream sources
- Anthropic MCP connector docs: https://platform.claude.com/docs/en/agents-and-tools/mcp-connector — confirms the
mcp_toolset tool type, the mcp-client-2025-11-20 beta header, and the exact response content block types "mcp_tool_use" and "mcp_tool_result" (example response blocks shown verbatim in the "How MCP connector tool calls work" section).
Local repo files inspected
py/src/braintrust/integrations/anthropic/tracing.py (full file, 1627 lines) — specifically _SERVER_TOOL_USE_TYPE (line 1337), _is_server_tool_result_type (line 1340), _log_server_tool_spans (line 1455), _MANAGED_AGENTS_CALL_TYPES (line 905)
py/src/braintrust/integrations/anthropic/integration.py
py/src/braintrust/integrations/anthropic/patchers.py
Summary
Anthropic's MCP connector feature (
tools=[{"type": "mcp_toolset", ...}]onclient.messages.create(), gated by themcp-client-2025-11-20beta header) returnsmcp_tool_useandmcp_tool_resultcontent blocks when Claude calls a remote MCP server's tools. The repo's Anthropic tracing does not recognizemcp_tool_useas a tool call at all, so:This is a correctness gap, not just missing-coverage: half of each MCP tool exchange is dropped and the other half is logged incompletely/incorrectly.
What is missing
In
py/src/braintrust/integrations/anthropic/tracing.py:_log_server_tool_spans(line 1455) pairs calls and results by walking response content:"server_tool_use"(used for built-in server tools like web search / code execution). It does not match"mcp_tool_use", somcp_tool_useblocks fall through the loop entirely and are never added tocalls_by_id._is_server_tool_result_type) matches anything ending in_tool_resultexcept the literaltool_result, somcp_tool_resultdoes pass this check — but since no matching call was ever registered, it's appended as(None, item), producing a tool span with output only and no input/tool name.Separately,
_MANAGED_AGENTS_CALL_TYPES(line 905) does include"agent.mcp_tool_use"— but that's the distinct,agent.-prefixed type used by the Managed Agents API (client.beta.agents/client.beta.sessions), not the plainmcp_tool_use/mcp_tool_resulttypes returned by the standard Messages API's MCP connector.Braintrust docs status:
unclear/not_foundThe Anthropic integration page mentions
mcp_serversexactly once, as one of many request parameters captured in span metadata for the Go SDK's request-param list. It does not mentionmcp_toolset,mcp_tool_use, ormcp_tool_resultanywhere, and does not document any tool-span behavior specific to the MCP connector for any language. The only documented span-splitting for server-side tools is generic ("server-side tool calls ... appear as child tool spans"), described for the Java SDK, and is not confirmed to apply to MCP connector blocks specifically.Upstream sources
mcp_toolsettool type, themcp-client-2025-11-20beta header, and the exact response content block types"mcp_tool_use"and"mcp_tool_result"(example response blocks shown verbatim in the "How MCP connector tool calls work" section).Local repo files inspected
py/src/braintrust/integrations/anthropic/tracing.py(full file, 1627 lines) — specifically_SERVER_TOOL_USE_TYPE(line 1337),_is_server_tool_result_type(line 1340),_log_server_tool_spans(line 1455),_MANAGED_AGENTS_CALL_TYPES(line 905)py/src/braintrust/integrations/anthropic/integration.pypy/src/braintrust/integrations/anthropic/patchers.py