Generated output schema uses Pydantic's validation shape while structured output uses its serialization shape

Initial Checks

• I confirm that I'm using the latest version of MCP Python SDK.
• I confirm that I searched existing issues and pull requests before opening this issue.

Description

For a Pydantic return model whose validation and serialization shapes differ, the generated outputSchema describes the validation shape while structuredContent uses the serialization shape. The SDK therefore publishes an output schema that rejects its own generated structured result.

This is related to, but not a duplicate of, #1073 / #1099. That change aligned ordinary field aliases by serializing structured output with aliases. Split validation_alias / serialization_alias values still expose different validation and serialization shapes, and serialization-only fields such as computed_field reveal the same underlying mismatch.

Example Code

from __future__ import annotations

import asyncio
import json

from jsonschema import Draft202012Validator
from pydantic import BaseModel, ConfigDict, Field, computed_field

try:
    from mcp.server.mcpserver.tools.base import Tool
except ImportError:  # MCP Python SDK 1.x
    from mcp.server.fastmcp.tools.base import Tool


class AliasOutput(BaseModel):
    model_config = ConfigDict(extra="forbid", populate_by_name=True)
    value: int = Field(validation_alias="wireIn", serialization_alias="wireOut")


def alias_output() -> AliasOutput:
    return AliasOutput(value=1)


class ComputedOutput(BaseModel):
    model_config = ConfigDict(extra="forbid")
    value: int

    @computed_field
    @property
    def doubled(self) -> int:
        return self.value * 2


def computed_output() -> ComputedOutput:
    return ComputedOutput(value=1)


async def check(function: object) -> None:
    tool = Tool.from_function(function)
    converted = await tool.run({}, None, convert_result=True)
    structured = converted[1] if isinstance(converted, tuple) else converted.structured_content
    errors = [
        error.message
        for error in Draft202012Validator(tool.output_schema).iter_errors(structured)
    ]
    print(function.__name__)
    print("schema:", json.dumps(tool.output_schema, sort_keys=True))
    print("structured:", json.dumps(structured, sort_keys=True))
    print("schema_errors:", errors)


async def main() -> None:
    await check(alias_output)
    await check(computed_output)


asyncio.run(main())

Observed validator messages:

alias_output
schema: ... "wireIn" ...
structured: {"wireOut": 1}
schema_errors: ["Additional properties are not allowed ('wireOut' was unexpected)", "'wireIn' is a required property"]

computed_output
schema: ... "value" ...
structured: {"doubled": 2, "value": 1}
schema_errors: ["Additional properties are not allowed ('doubled' was unexpected)"]

Expected behavior

The generated outputSchema should describe the serialized structured output. Generating the output model schema in Pydantic serialization mode makes both witnesses conform: the alias schema uses wireOut, and the computed-field schema includes doubled.

Python & MCP Python SDK

• Python: 3.13.13
• MCP Python SDK: 1.28.1 (latest stable)
• Also reproduced on current main: 2713b53b127afc094dc97d6067df9f69b647661c (2.0.0b2)
• Pydantic: 2.13.4

Beginne bei Tool.from_function in der Implementierung der MCP-Server-Tools, verwende die für die SDK-Versionen gezeigten Importpfade und verfolge, wie output_schema und structured_content erzeugt werden. Reproduziere die Beispiele alias_output und computed_output mit Draft202012Validator. Abgeschlossen ist die Aufgabe, wenn das generierte Schema beide serialisierten strukturierten Ergebnisse akzeptiert, einschließlich wireOut und doubled.