Client treats JSON-null structuredContent as missing, skipping outputSchema validation

Beginnen Sie bei ClientSession.validate_tool_result und untersuchen Sie, wie CallToolResult.model_fields_set zwischen ausgelassenem structuredContent und explizitem JSON null unterscheidet. Fügen Sie einen gezielten Validierungstest für ein outputSchema hinzu, das null erlaubt, oder aktualisieren Sie einen solchen Test, wobei die Fehlermeldung für ausgelassenen Inhalt erhalten bleiben muss; führen Sie die relevante SDK-Testsuite aus, um zu bestätigen, dass Schemaabweichungen weiterhin fehlschlagen.

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

On current main (57394b0548d1e2dc2dce8d67d84985769df3b8bb), ClientSession.validate_tool_result treats structured_content is None as "the tool did not return structured content".

That collapses two different wire shapes:

1. omitted structuredContent (field absent)
2. explicit JSON null ("structuredContent": null)

SEP-2106 / spec 2026-07-28 allow structuredContent to be any JSON value, including null. The TypeScript SDK already checks === undefined (not falsy / not null) for this reason.

Pydantic stores both omitted and JSON null as None. model_fields_set distinguishes them: a CallToolResult parsed from {"content": [], "structuredContent": null} has "structured_content" in model_fields_set, while an omitted field does not.

What happens today

• Tool advertises "outputSchema": {"type": "null"} (or {"type": ["object", "null"], ...}).
• Server returns "structuredContent": null.
• Client raises Tool {name} has an output schema but did not return structured content and never runs jsonschema against the value.

What I expected

• Omitted structuredContent still raises the existing missing-field error.
• Explicit JSON null is validated against the advertised schema: accept if the schema allows null, reject as a schema mismatch if it does not.
• Falsy JSON values (0, false, "") stay validated (they already are, because the current check is is None rather than falsy).

This is not #3224 (server injecting nulls for NotRequired keys). That issue is about serializing omitted object keys as null. This one is the client presence check before outputSchema validation.

I hit this while checking official SDK conformance of declared outputSchema against structuredContent. I have a small backwards-compatible test and fix ready and would like to send the PR if a maintainer wants it.

AI assistance: researched and drafted with Grok 4.6; I reviewed the spec text, the TypeScript v2 presence check, and the Pydantic model_fields_set behavior before filing.

Example Code

from mcp_types import CallToolResult

omitted = CallToolResult.model_validate({"content": []})
explicit_null = CallToolResult.model_validate({"content": [], "structuredContent": None})

assert omitted.structured_content is None
assert explicit_null.structured_content is None
assert "structured_content" not in omitted.model_fields_set
assert "structured_content" in explicit_null.model_fields_set

Against a tool whose outputSchema is {"type": "null"}, validate_tool_result currently raises the missing-field RuntimeError for explicit_null. After a presence check that uses model_fields_set, that result validates.

Python & MCP Python SDK

• Python 3.12
• MCP Python SDK main at 57394b0548d1e2dc2dce8d67d84985769df3b8bb (2.x)