3204201360
When a tool’s output TypedDict uses total=False, MCP clients reject the
response with:
```
MCP error -32602: Structured content does not match the tool's output schema
```
Note that the bug also exists for the Engine transport
(/worker/tools/execute), but since the engine doesn't validate the
output schema, the bug never surfaced. This PR addresses the problem
holistically (MCP and Engine) in preparation for a future where the
Engine transport validates output schemas.
Two bugs combined to cause this:
1. Schema: The outputSchema had no required array and declared all
fields as strict types (e.g. "type": "string"), making every field look
mandatory and non-null.
2. Serialization: model_dump() on TypedDict-derived Pydantic models
emitted None for absent optional fields. A tool returning {"name":
"hello"} produced {"name": "hello", "optional_field": null} which is a
value the schema forbids.
<!-- CURSOR_SUMMARY -->
---
> [!NOTE]
> **Medium Risk**
> Adjusts core schema generation and MCP JSON Schema conversion for
TypedDicts, affecting how tool input/output contracts are emitted and
validated across clients; mistakes could break compatibility or
validation behavior.
>
> **Overview**
> Fixes MCP/engine validation failures for `TypedDict(total=False)`
outputs by ensuring absent optional keys are **omitted from serialized
output** and that emitted schemas correctly describe **required vs
optional** keys.
>
> `arcade-core` now tracks `required_keys`/`inner_required_keys` and
per-field `nullable` in `ValueSchema`, derives required sets from
TypedDict `__required_keys__`, and unwraps `Optional[T]` to support
optional nested TypedDicts; TypedDict-derived Pydantic models now
`model_dump(exclude_unset=True)` to avoid leaking missing fields as
`null`.
>
> `arcade-mcp-server` JSON Schema conversion now emits `required` arrays
(including for arrays of objects), supports `nullable` by generating
`type: [<type>, "null"]` (and `enum` including `None`), and treats
nullable top-level objects as valid unwrapped output schemas. Adds
focused unit/end-to-end tests plus an expanded example server
demonstrating total-false, mixed required/optional, nullable, and
optional-nested TypedDict outputs, and bumps package
versions/dependencies accordingly.
>
> <sup>Reviewed by [Cursor Bugbot](https://cursor.com/bugbot) for commit
53fe8365f613053599130520b75f30b614b465ca. Bugbot is set up for automated
code reviews on this repo. Configure
[here](https://www.cursor.com/dashboard/bugbot).</sup>
<!-- /CURSOR_SUMMARY -->
44 lines
1.2 KiB
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44 lines
1.2 KiB
TOML
[project]
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name = "tools_with_output_schema"
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version = "0.1.0"
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description = "MCP Server created with Arcade.dev"
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requires-python = ">=3.10"
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dependencies = [
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"arcade-mcp-server>=1.19.1,<2.0.0",
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]
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[project.optional-dependencies]
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dev = [
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"arcade-mcp[all]>=1.12.1,<2.0.0",
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"pytest>=7.0.0",
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"pytest-asyncio>=0.21.0",
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"mypy>=1.0.0",
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"ruff>=0.1.0",
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]
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# Tell Arcade.dev that this package has Arcade tools
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[project.entry-points.arcade_toolkits]
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toolkit_name = "tools_with_output_schema"
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[tool.hatch.build.targets.wheel]
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packages = ["src/tools_with_output_schema"]
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[tool.ruff]
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line-length = 100
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target-version = "py312"
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[tool.mypy]
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python_version = "3.12"
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warn_unused_configs = true
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disallow_untyped_defs = false
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# Uncomment the following if you are developing inside of the arcade-mcp repo & want to use editable mode
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# Otherwise, you will install the following packages from PyPI
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# [tool.uv.sources]
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# arcade-mcp = { path = "../../../", editable = true }
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# arcade-serve = { path = "../../../libs/arcade-serve/", editable = true }
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# arcade-mcp-server = { path = "../../../libs/arcade-mcp-server/", editable = true }
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