modelcontextprotocol / modelcontextprotocol/python-sdk
Client treats JSON-null structuredContent as missing, skipping outputSchema validation
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Beschreibung
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:
- omitted
structuredContent(field absent) - 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 contentand never runs jsonschema against the value.
What I expected
- Omitted
structuredContentstill 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 isis Nonerather 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
mainat57394b0548d1e2dc2dce8d67d84985769df3b8bb(2.x)
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Rechercherichtung
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.
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Bewertung
- Tech-Stack
- python
- Bereich
- api
- Issue-Typ
- Bug
- Schwierigkeit
- 2/5
- Geschätzter Aufwand
- 1-3 Stunden
- Aktivitätsstatus
- Aktiv
- Klarheit
- Klar beschrieben
- Anfängerfreundlichkeit
- 75/100