siaochuan
6510a820a7
When non-Anthropic models (MiniMax, Moonshot, etc.) call MCP tools, they
sometimes send `null` for parameters they consider optional. The previous
implementation typed all fields as `object | None`, so:
1. Pydantic accepted `null` even for required fields (e.g. `query`)
2. `model_dump()` serialized these as `{"query": null, ...}`
3. The MCP server received null for required parameters → validation error
Fix:
- Map JSON Schema types to proper Python types (string→str, integer→int,
etc.) so Pydantic rejects null for required fields
- Use `exclude_none=True` in model_dump to strip optional null parameters
before passing to the MCP server
This affects ALL MCP tool servers, not just specific ones.
Tested with: MiniMax-M2.7-highspeed + dongtian MCP server (15 tools).
95 lines
3.2 KiB
Python
95 lines
3.2 KiB
Python
"""Tests for MCP tool adapters — input model generation and argument serialization."""
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import pytest
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from pydantic import ValidationError
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from openharness.tools.mcp_tool import _input_model_from_schema
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class TestInputModelFromSchema:
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"""Verify _input_model_from_schema maps JSON Schema types correctly."""
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def test_required_string_rejects_none(self):
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schema = {
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"type": "object",
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"properties": {"query": {"type": "string"}},
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"required": ["query"],
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}
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Model = _input_model_from_schema("search", schema)
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with pytest.raises(ValidationError):
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Model(query=None)
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def test_required_string_accepts_value(self):
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schema = {
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"type": "object",
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"properties": {"query": {"type": "string"}},
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"required": ["query"],
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}
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Model = _input_model_from_schema("search", schema)
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m = Model(query="zigzag")
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assert m.query == "zigzag"
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def test_optional_string_defaults_to_none(self):
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schema = {
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"type": "object",
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"properties": {
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"query": {"type": "string"},
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"wing": {"type": "string"},
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},
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"required": ["query"],
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}
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Model = _input_model_from_schema("search", schema)
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m = Model(query="test")
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assert m.wing is None
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def test_exclude_none_omits_optional_keeps_required(self):
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schema = {
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"type": "object",
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"properties": {
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"query": {"type": "string"},
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"wing": {"type": "string"},
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"limit": {"type": "integer"},
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},
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"required": ["query"],
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}
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Model = _input_model_from_schema("search", schema)
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m = Model(query="test")
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dumped = m.model_dump(mode="json", exclude_none=True)
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assert dumped == {"query": "test"}
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def test_all_json_types_mapped(self):
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schema = {
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"type": "object",
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"properties": {
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"name": {"type": "string"},
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"count": {"type": "integer"},
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"score": {"type": "number"},
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"active": {"type": "boolean"},
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"tags": {"type": "array"},
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"meta": {"type": "object"},
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},
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"required": ["name", "count", "score", "active", "tags", "meta"],
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}
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Model = _input_model_from_schema("full", schema)
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m = Model(name="x", count=1, score=0.5, active=True, tags=["a"], meta={"k": "v"})
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dumped = m.model_dump(mode="json")
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assert dumped == {
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"name": "x", "count": 1, "score": 0.5,
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"active": True, "tags": ["a"], "meta": {"k": "v"},
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}
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def test_empty_schema_creates_valid_model(self):
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Model = _input_model_from_schema("empty", {"type": "object"})
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m = Model()
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assert m.model_dump(mode="json") == {}
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def test_model_rejects_null_for_required_integer(self):
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schema = {
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"type": "object",
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"properties": {"limit": {"type": "integer"}},
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"required": ["limit"],
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}
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Model = _input_model_from_schema("limited", schema)
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with pytest.raises(ValidationError):
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Model(limit=None)
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