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func_metadata raises uncaught PydanticSchemaGenerationError for Iterator/AsyncIterator tool return annotations instead of the unstructured fallback #3573
Description
Initial Checks
- I confirm that I'm using the newest release of my line (the latest 2.x, or the latest 1.x if I'm still on v1)
- I confirm that I searched for my issue in https://github.com/modelcontextprotocol/python-sdk/issues before opening this issue
Release line
2.x (current stable)
Description
Registering a tool whose function is annotated -> Iterator[...] or -> AsyncIterator[...] — the PEP 484 spelling for generator functions — raises a raw pydantic.errors.PydanticSchemaGenerationError at registration time, instead of either falling back to an unstructured tool (structured_output=None, the default) or raising the SDK's InvalidSignature (structured_output=True). The same happens via @server.tool() / Tool.from_function(), so a properly typed generator tool cannot be registered at all.
Actual output of the script in "Example Code" (error text truncated at 80 chars by the script):
func_metadata(search): UNCAUGHT pydantic.errors.PydanticSchemaGenerationError: Unable to generate pydantic-core schema for typing.Iterator[str]. Set `arbitrary
func_metadata(search, structured_output=True): UNCAUGHT pydantic.errors.PydanticSchemaGenerationError: Unable to generate pydantic-core schema for typing.Iterator[str]. Set `arbitrary
Tool.from_function(search): UNCAUGHT pydantic.errors.PydanticSchemaGenerationError: Unable to generate pydantic-core schema for typing.Iterator[str]. Set `arbitrary
Full traceback (captured with the collections.abc spelling of the same annotation, so the error names it accordingly):
File "src/mcp/server/mcpserver/utilities/func_metadata.py", line 444, in func_metadata
output_model, wrap_output = _create_output_model(original_annotation, return_type_expr, func.__name__)
File "src/mcp/server/mcpserver/utilities/func_metadata.py", line 550, in _create_output_model
model = _create_wrapped_model(func_name, original_annotation)
File "src/mcp/server/mcpserver/utilities/func_metadata.py", line 621, in _create_wrapped_model
return create_model(model_name, result=annotation)
pydantic.errors.PydanticSchemaGenerationError: Unable to generate pydantic-core schema for collections.abc.Iterator[str]. Set `arbitrary_types_allowed=True` in the model_config to ignore this error or implement `__get_pydantic_core_schema__` on your type to fully support it.
What I expected is what already happens for other unserializable return types, pinned by test_structured_output_unserializable_type_error (tests/server/mcpserver/test_func_metadata.py:1233, passes on main) and documented in docs/servers/structured-output.md: with structured_output=None, registration succeeds and output_schema is None (fallback to text); with structured_output=True, InvalidSignature: Function search: return type ... is not serializable for structured output. For contrast, Iterable[str] and Generator[str, None, None] both register successfully through the same wrapped-model path — only the PEP 484-recommended spellings for generators crash.
Root cause: _create_output_model(...) is called at src/mcp/server/mcpserver/utilities/func_metadata.py:444, outside the try/except at lines 446–470 whose except tuple (PydanticUserError, pydantic_core.SchemaError, ...) exists exactly so that "an unsupported return type surfaces here, at registration" as a clean failure. _create_output_model → _create_wrapped_model → create_model(model_name, result=annotation) (line 621) builds a schema itself, and its PydanticSchemaGenerationError (a PydanticUserError subclass) escapes uncaught. Moving the line 444 call inside the existing try/except looks like it would restore both documented behaviours; I'd be happy to be assigned and open a PR with that approach.
Related: the guard was added in #2434 (for #1131), but it wraps only the FuncMetadata construction, not this call. #1060 reports the same error class for a different type (Image, 1.x fastmcp) and looks unrelated to this code path.
AI disclosure: this issue and its reproduction were prepared with AI assistance.
Example Code
from typing import Iterator
from mcp.server.mcpserver.tools import Tool
from mcp.server.mcpserver.utilities.func_metadata import func_metadata
def search(n: int) -> Iterator[str]:
yield from ["a"] * n
for label, call in [
("func_metadata(search)", lambda: func_metadata(search)),
("func_metadata(search, structured_output=True)", lambda: func_metadata(search, structured_output=True)),
("Tool.from_function(search)", lambda: Tool.from_function(search)),
]:
try:
call()
print(f"{label}: OK")
except Exception as e:
print(f"{label}: UNCAUGHT {type(e).__module__}.{type(e).__name__}: {str(e)[:80]}")
# AsyncIterator[str] return annotations behave identicallyPython & MCP Python SDK
mcp: main @ 6affe5c0d3588fd1705713b3703dc68015cfe3eb
func_metadata.py is identical in v2.2.0 (latest 2.x release);
the same crash reproduces on a fresh `pip install mcp==2.2.0`
Python 3.13.15
pydantic 2.12.5
macOS 26.6.2 (arm64)
Activity
JingHao-Leon commentedon Sep 23, 2026
Confirmed on mcp 2.2.0 — all three registration shapes raise the raw
pydantic.errors.PydanticSchemaGenerationErrorforcollections.abc.Iterator[str]/AsyncIterator[str]returns (func_metadata(search),func_metadata(search, structured_output=True), and theTool.from_functionpath).The traceback pins exactly where the intended fallback is defeated. In
mcp/server/mcpserver/utilities/func_metadata.py:Two things make this a straightforward fix:
The raise happens at L444, outside the guarded region. The
try/exceptat L447-469 exists precisely to turn unsupported return types into a graceful outcome, andPydanticSchemaGenerationError(aPydanticUserErrorsubclass on pydantic 2.13) is already covered conceptually by its caught types — but_create_output_modelruns before thetry, so_create_wrapped_model'screate_modelcall escapes unprotected. Both intended behaviors are defeated by the same escape: the unstructured fallback (return FuncMetadata(arg_model=arguments_model), L477) and, forstructured_output=True, the properInvalidSignature(L471-475).Iterator returns aren't recognized as content-iterators. The early-out at L437 (
if structured_output is None and _returns_content(return_type_expr)) returns an unstructuredFuncMetadatafor annotations the model reads as content — but it doesn't match the PEP 484 generator spellingsIterator[...]/AsyncIterator[...], so they fall through into schema construction instead.Wrapping the
_create_output_modelcall in the existing except handling would restore both documented behaviors with one change; optionally treatingIterator/AsyncIteratororigins in_returns_contentwould give generator tools the same unstructured default as content-block returns.BlueX888 commentedon Sep 23, 2026
Reproduced this. Root cause: src/mcp/server/mcpserver/utilities/func_metadata.py:444 calls _create_output_model outside the try/except at lines 446-470 that reports unserializable return types at registration, so the PydanticSchemaGenerationError it raises for Iterator/AsyncIterator escapes func_metadata uncaught.
Minimal reproduction:
Observed output:
Fix is ready on
BlueX888:fix/prep-func-metadata-iterator-return-uncaught-pydantic-error(commit2f4ce1ae). Moves the _create_output_model call inside that existing try/except, so Iterator/AsyncIterator returns follow the documented contract: no output schema by default, InvalidSignature with structured_output=True.Verified with:
uv run --frozen pytest tests/server/mcpserver/test_func_metadata.pyHappy to open the PR once you confirm the approach or assign this to me.
0xamlab commentedon Sep 25, 2026
Confirmed on mcp 2.2.0 with the v2 API (
MCPServer): both the default path andstructured_output=Trueraise the rawPydanticSchemaGenerationErrorat registration for a-> Iterator[str]tool — the generator tool simply cannot be registered at all.Minimal repro:
→
PydanticSchemaGenerationError: Unable to generate pydantic-core schema for typing.Iterator[str]. Same forstructured_output=True.The contract says the default should fall back to an unstructured tool (
structured_output=None), andstructured_output=Trueshould raise the SDK's ownInvalidSignature— a raw pydantic error escapes both. Root-cause candidate:func_metadata's return-type schema generation treatsIterator/AsyncIteratoras a schema-able output type instead of short-circuiting to the generator/unstructured path first.Happy to open a PR with a failing test first (both spellings must register without raising;
structured_output=Truemust surfaceInvalidSignature) plus the narrow fix, if a maintainer assigns the issue — the repo's bot auto-closes non-assignee PRs, so I'm holding the branch until then.Affiliation: we ship a 140-tool MCP server and hit this exact class of annotation edge case in our own tool registry.
Rainmemery commentedon Sep 26, 2026
Confirmed on Windows 11 / Python 3.13 / pydantic 2.12.5 against
main(f1b6589) — all four spellings crash at registration, with both the default andstructured_output=True:The escape point matches @BlueX888's analysis: the
_create_output_model()call (func_metadata.py:444on main) sits outside thetryat :446 that routes expected schema failures to the unstructured fallback, so thePydanticSchemaGenerationErrorraised bycreate_model(..., result=Iterator[str])inside_create_wrapped_model()escapesfunc_metadataentirely.The fix that keeps the existing semantics is to route that call through the same failure path: on
PydanticSchemaGenerationError, degrade to the unstructured fallback (output_model=None), which also makesstructured_output=TrueraiseInvalidSignaturevia the existing check. Two notes from testing this locally:typing.Iterator[str](typing._GenericAlias) andcollections.abc.Iterator[str](types.GenericAlias) take different branches in_create_output_modelbut end at the samecreate_modelcrash.Generator[str, None, None]is unaffected: pydantic models it as a sequence, so it builds the wrapped{"result": [...]}schema today and keeps doing so after the fix.I have this working locally with regression tests for all four spellings plus the
Generatorcontrast — a PR is up at #3587 linking this issue.Disclosure: this was developed with AI assistance; I have reviewed the diff and run the tests locally.