fastmcp/tests/tools/test_tool.py

1489 lines
54 KiB
Python

import json
from dataclasses import dataclass
from typing import Annotated, Any
import pytest
from mcp.types import (
AudioContent,
EmbeddedResource,
ImageContent,
TextContent,
TextResourceContents,
)
from pydantic import AnyUrl, BaseModel, Field, TypeAdapter
from typing_extensions import TypedDict
from fastmcp.tools.tool import Tool, _convert_to_content
from fastmcp.utilities.json_schema import compress_schema
from fastmcp.utilities.tests import caplog_for_fastmcp
from fastmcp.utilities.types import Audio, File, Image
class TestToolFromFunction:
def test_basic_function(self):
"""Test registering and running a basic function."""
def add(a: int, b: int) -> int:
"""Add two numbers."""
return a + b
tool = Tool.from_function(add)
assert tool.name == "add"
assert tool.description == "Add two numbers."
assert len(tool.parameters["properties"]) == 2
assert tool.parameters["properties"]["a"]["type"] == "integer"
assert tool.parameters["properties"]["b"]["type"] == "integer"
# With primitive wrapping, int return type becomes object with result property
expected_schema = {
"type": "object",
"properties": {"result": {"type": "integer", "title": "Result"}},
"required": ["result"],
"title": "_WrappedResult",
"x-fastmcp-wrap-result": True,
}
assert tool.output_schema == expected_schema
def test_meta_parameter(self):
"""Test that meta parameter is properly handled."""
def multiply(a: int, b: int) -> int:
"""Multiply two numbers."""
return a * b
meta_data = {"version": "1.0", "author": "test"}
tool = Tool.from_function(multiply, meta=meta_data)
assert tool.meta == meta_data
mcp_tool = tool.to_mcp_tool()
# MCP tool includes fastmcp meta, so check that our meta is included
assert mcp_tool.meta is not None
assert meta_data.items() <= mcp_tool.meta.items()
async def test_async_function(self):
"""Test registering and running an async function."""
async def fetch_data(url: str) -> str:
"""Fetch data from URL."""
return f"Data from {url}"
tool = Tool.from_function(fetch_data)
assert tool.name == "fetch_data"
assert tool.description == "Fetch data from URL."
assert tool.parameters["properties"]["url"]["type"] == "string"
def test_callable_object(self):
class Adder:
"""Adds two numbers."""
def __call__(self, x: int, y: int) -> int:
"""ignore this"""
return x + y
tool = Tool.from_function(Adder())
assert tool.name == "Adder"
assert tool.description == "Adds two numbers."
assert len(tool.parameters["properties"]) == 2
assert tool.parameters["properties"]["x"]["type"] == "integer"
assert tool.parameters["properties"]["y"]["type"] == "integer"
def test_async_callable_object(self):
class Adder:
"""Adds two numbers."""
async def __call__(self, x: int, y: int) -> int:
"""ignore this"""
return x + y
tool = Tool.from_function(Adder())
assert tool.name == "Adder"
assert tool.description == "Adds two numbers."
assert len(tool.parameters["properties"]) == 2
assert tool.parameters["properties"]["x"]["type"] == "integer"
assert tool.parameters["properties"]["y"]["type"] == "integer"
def test_pydantic_model_function(self):
"""Test registering a function that takes a Pydantic model."""
class UserInput(BaseModel):
name: str
age: int
def create_user(user: UserInput, flag: bool) -> dict:
"""Create a new user."""
return {"id": 1, **user.model_dump()}
tool = Tool.from_function(create_user)
assert tool.name == "create_user"
assert tool.description == "Create a new user."
assert "name" in tool.parameters["$defs"]["UserInput"]["properties"]
assert "age" in tool.parameters["$defs"]["UserInput"]["properties"]
assert "flag" in tool.parameters["properties"]
async def test_tool_with_image_return(self):
def image_tool(data: bytes) -> Image:
return Image(data=data)
tool = Tool.from_function(image_tool)
result = await tool.run({"data": "test.png"})
assert tool.parameters["properties"]["data"]["type"] == "string"
assert isinstance(result.content[0], ImageContent)
async def test_tool_with_audio_return(self):
def audio_tool(data: bytes) -> Audio:
return Audio(data=data)
tool = Tool.from_function(audio_tool)
result = await tool.run({"data": "test.wav"})
assert tool.parameters["properties"]["data"]["type"] == "string"
assert isinstance(result.content[0], AudioContent)
async def test_tool_with_file_return(self):
def file_tool(data: bytes) -> File:
return File(data=data, format="octet-stream")
tool = Tool.from_function(file_tool)
result = await tool.run({"data": "test.bin"})
assert tool.parameters["properties"]["data"]["type"] == "string"
assert len(result.content) == 1
assert isinstance(result.content[0], EmbeddedResource)
assert result.content[0].type == "resource"
assert hasattr(result.content[0], "resource")
resource = result.content[0].resource
assert resource.mimeType == "application/octet-stream"
def test_non_callable_fn(self):
with pytest.raises(TypeError, match="not a callable object"):
Tool.from_function(1) # type: ignore
def test_lambda(self):
tool = Tool.from_function(lambda x: x, name="my_tool")
assert tool.name == "my_tool"
def test_lambda_with_no_name(self):
with pytest.raises(
ValueError, match="You must provide a name for lambda functions"
):
Tool.from_function(lambda x: x)
def test_private_arguments(self):
def add(_a: int, _b: int) -> int:
"""Add two numbers."""
return _a + _b
tool = Tool.from_function(add)
assert tool.parameters["properties"]["_a"]["type"] == "integer"
assert tool.parameters["properties"]["_b"]["type"] == "integer"
def test_tool_with_varargs_not_allowed(self):
def func(a: int, b: int, *args: int) -> int:
"""Add two numbers."""
return a + b
with pytest.raises(
ValueError, match=r"Functions with \*args are not supported as tools"
):
Tool.from_function(func)
def test_tool_with_varkwargs_not_allowed(self):
def func(a: int, b: int, **kwargs: int) -> int:
"""Add two numbers."""
return a + b
with pytest.raises(
ValueError, match=r"Functions with \*\*kwargs are not supported as tools"
):
Tool.from_function(func)
async def test_instance_method(self):
class MyClass:
def add(self, x: int, y: int) -> int:
"""Add two numbers."""
return x + y
obj = MyClass()
tool = Tool.from_function(obj.add)
assert tool.name == "add"
assert tool.description == "Add two numbers."
assert "self" not in tool.parameters["properties"]
async def test_instance_method_with_varargs_not_allowed(self):
class MyClass:
def add(self, x: int, y: int, *args: int) -> int:
"""Add two numbers."""
return x + y
obj = MyClass()
with pytest.raises(
ValueError, match=r"Functions with \*args are not supported as tools"
):
Tool.from_function(obj.add)
async def test_instance_method_with_varkwargs_not_allowed(self):
class MyClass:
def add(self, x: int, y: int, **kwargs: int) -> int:
"""Add two numbers."""
return x + y
obj = MyClass()
with pytest.raises(
ValueError, match=r"Functions with \*\*kwargs are not supported as tools"
):
Tool.from_function(obj.add)
async def test_classmethod(self):
class MyClass:
x: int = 10
@classmethod
def call(cls, x: int, y: int) -> int:
"""Add two numbers."""
return x + y
tool = Tool.from_function(MyClass.call)
assert tool.name == "call"
assert tool.description == "Add two numbers."
assert "x" in tool.parameters["properties"]
assert "y" in tool.parameters["properties"]
async def test_tool_serializer(self):
"""Test that a tool's serializer is used to serialize the result."""
def custom_serializer(data) -> str:
return f"Custom serializer: {data}"
def process_list(items: list[int]) -> int:
return sum(items)
tool = Tool.from_function(process_list, serializer=custom_serializer)
result = await tool.run(arguments={"items": [1, 2, 3, 4, 5]})
# Custom serializer affects unstructured content
assert isinstance(result.content[0], TextContent)
assert result.content[0].text == "Custom serializer: 15"
# Structured output should have the raw value
assert result.structured_content == {"result": 15}
class TestToolFromFunctionOutputSchema:
async def test_no_return_annotation(self):
def func():
pass
tool = Tool.from_function(func)
assert tool.output_schema is None
@pytest.mark.parametrize(
"annotation",
[
int,
float,
bool,
str,
int | float,
list,
list[int],
list[int | float],
dict,
dict[str, Any],
dict[str, int | None],
tuple[int, str],
set[int],
list[tuple[int, str]],
],
)
async def test_simple_return_annotation(self, annotation):
def func() -> annotation: # type: ignore
return 1
tool = Tool.from_function(func)
base_schema = TypeAdapter(annotation).json_schema()
# Non-object types get wrapped
schema_type = base_schema.get("type")
is_object_type = schema_type == "object"
if not is_object_type:
# Non-object types get wrapped
expected_schema = {
"type": "object",
"properties": {"result": {**base_schema, "title": "Result"}},
"required": ["result"],
"title": "_WrappedResult",
"x-fastmcp-wrap-result": True,
}
assert tool.output_schema == expected_schema
else:
# Object types remain unwrapped
assert tool.output_schema == base_schema
@pytest.mark.parametrize(
"annotation",
[
AnyUrl,
Annotated[int, Field(ge=1)],
Annotated[int, Field(ge=1)],
],
)
async def test_complex_return_annotation(self, annotation):
def func() -> annotation: # type: ignore
return 1
tool = Tool.from_function(func)
base_schema = TypeAdapter(annotation).json_schema()
expected_schema = {
"type": "object",
"properties": {"result": {**base_schema, "title": "Result"}},
"required": ["result"],
"title": "_WrappedResult",
"x-fastmcp-wrap-result": True,
}
assert tool.output_schema == expected_schema
async def test_none_return_annotation(self):
def func() -> None:
pass
tool = Tool.from_function(func)
assert tool.output_schema is None
async def test_any_return_annotation(self):
def func() -> Any:
return 1
tool = Tool.from_function(func)
assert tool.output_schema is None
@pytest.mark.parametrize(
"annotation, expected",
[
(Image, ImageContent),
(Audio, AudioContent),
(File, EmbeddedResource),
(Image | int, ImageContent | int),
(Image | Audio, ImageContent | AudioContent),
(list[Image | Audio], list[ImageContent | AudioContent]),
],
)
async def test_converted_return_annotation(self, annotation, expected):
def func() -> annotation: # type: ignore
return 1
tool = Tool.from_function(func)
# Image, Audio, File types don't generate output schemas since they're converted to content directly
assert tool.output_schema is None
async def test_dataclass_return_annotation(self):
@dataclass
class Person:
name: str
age: int
def func() -> Person:
return Person(name="John", age=30)
tool = Tool.from_function(func)
expected_schema = compress_schema(TypeAdapter(Person).json_schema())
assert tool.output_schema == expected_schema
async def test_base_model_return_annotation(self):
class Person(BaseModel):
name: str
age: int
def func() -> Person:
return Person(name="John", age=30)
tool = Tool.from_function(func)
expected_schema = compress_schema(TypeAdapter(Person).json_schema())
assert tool.output_schema == expected_schema
async def test_typeddict_return_annotation(self):
class Person(TypedDict):
name: str
age: int
def func() -> Person:
return Person(name="John", age=30)
tool = Tool.from_function(func)
expected_schema = compress_schema(TypeAdapter(Person).json_schema())
assert tool.output_schema == expected_schema
async def test_unserializable_return_annotation(self):
class Unserializable:
def __init__(self, data: Any):
self.data = data
def func() -> Unserializable:
return Unserializable(data="test")
tool = Tool.from_function(func)
assert tool.output_schema is None
async def test_mixed_unserializable_return_annotation(self):
class Unserializable:
def __init__(self, data: Any):
self.data = data
def func() -> Unserializable | int:
return Unserializable(data="test")
tool = Tool.from_function(func)
assert tool.output_schema is None
async def test_provided_output_schema_takes_precedence_over_json_compatible_annotation(
self,
):
"""Test that provided output_schema takes precedence over inferred schema from JSON-compatible annotation."""
def func() -> dict[str, int]:
return {"a": 1, "b": 2}
# Provide a custom output schema that differs from the inferred one
custom_schema = {"type": "object", "description": "Custom schema"}
tool = Tool.from_function(func, output_schema=custom_schema)
assert tool.output_schema == custom_schema
async def test_provided_output_schema_takes_precedence_over_complex_annotation(
self,
):
"""Test that provided output_schema takes precedence over inferred schema from complex annotation."""
def func() -> list[dict[str, int | float]]:
return [{"a": 1, "b": 2.5}]
# Provide a custom output schema that differs from the inferred one
custom_schema = {"type": "object", "properties": {"custom": {"type": "string"}}}
tool = Tool.from_function(func, output_schema=custom_schema)
assert tool.output_schema == custom_schema
async def test_provided_output_schema_takes_precedence_over_unserializable_annotation(
self,
):
"""Test that provided output_schema takes precedence over None schema from unserializable annotation."""
class Unserializable:
def __init__(self, data: Any):
self.data = data
def func() -> Unserializable:
return Unserializable(data="test")
# Provide a custom output schema even though the annotation is unserializable
custom_schema = {
"type": "object",
"properties": {"items": {"type": "array", "items": {"type": "string"}}},
}
tool = Tool.from_function(func, output_schema=custom_schema)
assert tool.output_schema == custom_schema
async def test_provided_output_schema_takes_precedence_over_no_annotation(self):
"""Test that provided output_schema takes precedence over None schema from no annotation."""
def func():
return "hello"
# Provide a custom output schema even though there's no return annotation
custom_schema = {
"type": "object",
"properties": {"value": {"type": "number", "minimum": 0}},
}
tool = Tool.from_function(func, output_schema=custom_schema)
assert tool.output_schema == custom_schema
async def test_provided_output_schema_takes_precedence_over_converted_annotation(
self,
):
"""Test that provided output_schema takes precedence over converted schema from Image/Audio/File annotations."""
def func() -> Image:
return Image(data=b"test")
# Provide a custom output schema that differs from the converted ImageContent schema
custom_schema = {
"type": "object",
"properties": {"custom_image": {"type": "string"}},
}
tool = Tool.from_function(func, output_schema=custom_schema)
assert tool.output_schema == custom_schema
async def test_provided_output_schema_takes_precedence_over_union_annotation(self):
"""Test that provided output_schema takes precedence over inferred schema from union annotation."""
def func() -> str | int | None:
return "hello"
# Provide a custom output schema that differs from the inferred union schema
custom_schema = {"type": "object", "properties": {"flag": {"type": "boolean"}}}
tool = Tool.from_function(func, output_schema=custom_schema)
assert tool.output_schema == custom_schema
async def test_provided_output_schema_takes_precedence_over_pydantic_annotation(
self,
):
"""Test that provided output_schema takes precedence over inferred schema from Pydantic model annotation."""
class Person(BaseModel):
name: str
age: int
def func() -> Person:
return Person(name="John", age=30)
# Provide a custom output schema that differs from the inferred Person schema
custom_schema = {
"type": "object",
"properties": {"numbers": {"type": "array", "items": {"type": "number"}}},
}
tool = Tool.from_function(func, output_schema=custom_schema)
assert tool.output_schema == custom_schema
async def test_output_schema_false_allows_automatic_structured_content(self):
"""Test that output_schema=False still allows automatic structured content for dict-like objects."""
def func() -> dict[str, str]:
return {"message": "Hello, world!"}
tool = Tool.from_function(func, output_schema=None)
assert tool.output_schema is None
result = await tool.run({})
# Dict objects automatically become structured content even without schema
assert result.structured_content == {"message": "Hello, world!"}
assert len(result.content) == 1
assert result.content[0].text == '{"message":"Hello, world!"}' # type: ignore[attr-defined]
async def test_output_schema_none_disables_structured_content(self):
"""Test that output_schema=None explicitly disables structured content."""
def func() -> int:
return 42
tool = Tool.from_function(func, output_schema=None)
assert tool.output_schema is None
result = await tool.run({})
assert result.structured_content is None
assert len(result.content) == 1
assert result.content[0].text == "42" # type: ignore[attr-defined]
async def test_output_schema_inferred_when_not_specified(self):
"""Test that output schema is inferred when not explicitly specified."""
def func() -> int:
return 42
# Don't specify output_schema - should infer and wrap
tool = Tool.from_function(func)
expected_schema = {
"type": "object",
"properties": {"result": {"type": "integer", "title": "Result"}},
"required": ["result"],
"title": "_WrappedResult",
"x-fastmcp-wrap-result": True,
}
assert tool.output_schema == expected_schema
result = await tool.run({})
assert result.structured_content == {"result": 42}
async def test_explicit_object_schema_with_dict_return(self):
"""Test that explicit object schemas work when function returns a dict."""
def func() -> dict[str, int]:
return {"value": 42}
# Provide explicit object schema
explicit_schema = {
"type": "object",
"properties": {"value": {"type": "integer", "minimum": 0}},
}
tool = Tool.from_function(func, output_schema=explicit_schema)
assert tool.output_schema == explicit_schema # Schema not wrapped
assert tool.output_schema and "x-fastmcp-wrap-result" not in tool.output_schema
result = await tool.run({})
# Dict result with object schema is used directly
assert result.structured_content == {"value": 42}
assert result.content[0].text == '{"value":42}' # type: ignore[attr-defined]
async def test_explicit_object_schema_with_non_dict_return_fails(self):
"""Test that explicit object schemas fail when function returns non-dict."""
def func() -> int:
return 42
# Provide explicit object schema but return non-dict
explicit_schema = {
"type": "object",
"properties": {"value": {"type": "integer"}},
}
tool = Tool.from_function(func, output_schema=explicit_schema)
# Should fail because int is not dict-compatible with object schema
with pytest.raises(ValueError, match="structured_content must be a dict"):
await tool.run({})
async def test_object_output_schema_not_wrapped(self):
"""Test that object-type output schemas are never wrapped."""
def func() -> dict[str, int]:
return {"value": 42}
# Object schemas should never be wrapped, even when inferred
tool = Tool.from_function(func)
expected_schema = TypeAdapter(dict[str, int]).json_schema()
assert tool.output_schema == expected_schema # Not wrapped
assert tool.output_schema and "x-fastmcp-wrap-result" not in tool.output_schema
result = await tool.run({})
assert result.structured_content == {"value": 42} # Direct value
async def test_structured_content_interaction_with_wrapping(self):
"""Test that structured content works correctly with schema wrapping."""
def func() -> str:
return "hello"
# Inferred schema should wrap string type
tool = Tool.from_function(func)
expected_schema = {
"type": "object",
"properties": {"result": {"type": "string", "title": "Result"}},
"required": ["result"],
"title": "_WrappedResult",
"x-fastmcp-wrap-result": True,
}
assert tool.output_schema == expected_schema
result = await tool.run({})
# Unstructured content
assert len(result.content) == 1
assert result.content[0].text == "hello" # type: ignore[attr-defined]
# Structured content should be wrapped
assert result.structured_content == {"result": "hello"}
async def test_structured_content_with_explicit_object_schema(self):
"""Test structured content with explicit object schema."""
def func() -> dict[str, str]:
return {"greeting": "hello"}
# Provide explicit object schema
explicit_schema = {
"type": "object",
"properties": {"greeting": {"type": "string"}},
"required": ["greeting"],
}
tool = Tool.from_function(func, output_schema=explicit_schema)
assert tool.output_schema == explicit_schema
result = await tool.run({})
# Should use direct value since explicit schema doesn't have wrap marker
assert result.structured_content == {"greeting": "hello"}
async def test_structured_content_with_custom_wrapper_schema(self):
"""Test structured content with custom schema that includes wrap marker."""
def func() -> str:
return "world"
# Custom schema with wrap marker
custom_schema = {
"type": "object",
"properties": {"message": {"type": "string"}},
"x-fastmcp-wrap-result": True,
}
tool = Tool.from_function(func, output_schema=custom_schema)
assert tool.output_schema == custom_schema
result = await tool.run({})
# Should wrap with "result" key due to wrap marker
assert result.structured_content == {"result": "world"}
async def test_none_vs_false_output_schema_behavior(self):
"""Test the difference between None and False for output_schema."""
def func() -> int:
return 123
# None should disable
tool_none = Tool.from_function(func, output_schema=None)
assert tool_none.output_schema is None
# Default (NotSet) should infer from return type
tool_default = Tool.from_function(func)
assert (
tool_default.output_schema is not None
) # Should infer schema from dict return type
# Different behavior: None vs inferred
result_none = await tool_none.run({})
result_default = await tool_default.run({})
# None should still try fallback generation but fail for non-dict
assert result_none.structured_content is None # Fallback fails for int
# Default should use proper schema and wrap the result
assert result_default.structured_content == {
"result": 123
} # Schema-based generation with wrapping
assert result_none.content[0].text == result_default.content[0].text == "123" # type: ignore[attr-defined]
async def test_non_object_output_schema_raises_error(self):
"""Test that providing a non-object output schema raises a ValueError."""
def func() -> int:
return 42
# Test various non-object schemas that should raise errors
non_object_schemas = [
{"type": "string"},
{"type": "integer", "minimum": 0},
{"type": "number"},
{"type": "boolean"},
{"type": "array", "items": {"type": "string"}},
]
for schema in non_object_schemas:
with pytest.raises(
ValueError, match='Output schemas must have "type" set to "object"'
):
Tool.from_function(func, output_schema=schema)
class TestConvertResultToContent:
"""Tests for the _convert_to_content helper function."""
def test_none_result(self):
"""Test that None results in an empty list."""
result = _convert_to_content(None)
assert isinstance(result, list)
assert len(result) == 0
def test_text_content_result(self):
"""Test that TextContent is returned as a list containing itself."""
content = TextContent(type="text", text="hello")
result = _convert_to_content(content)
assert isinstance(result, list)
assert len(result) == 1
assert result[0] is content
def test_image_content_result(self):
"""Test that ImageContent is returned as a list containing itself."""
content = ImageContent(type="image", data="fakeimagedata", mimeType="image/png")
result = _convert_to_content(content)
assert isinstance(result, list)
assert len(result) == 1
assert result[0] is content
def test_embedded_resource_result(self):
"""Test that EmbeddedResource is returned as a list containing itself."""
content = EmbeddedResource(
type="resource",
resource=TextResourceContents(
uri=AnyUrl("resource://test"),
mimeType="text/plain",
text="resource content",
),
)
result = _convert_to_content(content)
assert isinstance(result, list)
assert len(result) == 1
assert result[0] is content
def test_image_object_result(self):
"""Test that an Image object is converted to ImageContent."""
image_obj = Image(data=b"fakeimagedata")
result = _convert_to_content(image_obj)
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], ImageContent)
assert result[0].data == "ZmFrZWltYWdlZGF0YQ=="
def test_audio_object_result(self):
"""Test that an Audio object is converted to AudioContent."""
audio_obj = Audio(data=b"fakeaudiodata")
result = _convert_to_content(audio_obj)
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], AudioContent)
assert result[0].data == "ZmFrZWF1ZGlvZGF0YQ=="
def test_file_object_result(self):
"""Test that a File object is converted to EmbeddedResource with BlobResourceContents."""
file_obj = File(data=b"filedata", format="octet-stream")
result = _convert_to_content(file_obj)
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], EmbeddedResource)
assert result[0].type == "resource"
assert hasattr(result[0], "resource")
resource = result[0].resource
assert resource.mimeType == "application/octet-stream"
# Check for blob attribute and its value
assert hasattr(resource, "blob")
assert getattr(resource, "blob") == "ZmlsZWRhdGE=" # base64 encoded "filedata"
# Convert URI to string for startswith check
assert str(resource.uri).startswith("file:///resource.octet-stream")
def test_file_object_text_result(self):
"""Test that a File object with text data is converted to EmbeddedResource with TextResourceContents."""
file_obj = File(data=b"sometext", format="plain")
result = _convert_to_content(file_obj)
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], EmbeddedResource)
assert result[0].type == "resource"
resource = result[0].resource
assert isinstance(resource, TextResourceContents)
assert resource.mimeType == "text/plain"
assert resource.text == "sometext"
def test_basic_type_result(self):
"""Test that a basic type is converted to TextContent."""
result = _convert_to_content(123)
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], TextContent)
assert result[0].text == "123"
result = _convert_to_content("hello")
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], TextContent)
assert result[0].text == "hello"
result = _convert_to_content({"a": 1, "b": 2})
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], TextContent)
assert result[0].text == '{"a":1,"b":2}'
def test_list_of_basic_types(self):
"""Test that a list of basic types is converted to a single TextContent."""
result = _convert_to_content([1, "two", {"c": 3}])
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], TextContent)
assert result[0].text == '[1,"two",{"c":3}]'
def test_list_of_mcp_types(self):
"""Test that a list of MCP types is returned as a list of those types."""
content1 = TextContent(type="text", text="hello")
content2 = ImageContent(
type="image", data="fakeimagedata2", mimeType="image/png"
)
result = _convert_to_content([content1, content2])
assert isinstance(result, list)
assert len(result) == 2
assert result[0] is content1
assert result[1] is content2
def test_list_of_mixed_types(self):
"""Test that a list of mixed types is converted correctly."""
content1 = TextContent(type="text", text="hello")
image_obj = Image(data=b"fakeimagedata")
basic_data = {"a": 1}
result = _convert_to_content([content1, image_obj, basic_data])
assert isinstance(result, list)
assert len(result) == 3
text_content_count = sum(isinstance(item, TextContent) for item in result)
image_content_count = sum(isinstance(item, ImageContent) for item in result)
assert text_content_count == 2
assert image_content_count == 1
text_item = next(item for item in result if isinstance(item, TextContent))
assert text_item.text == '[{"a":1}]'
image_item = next(item for item in result if isinstance(item, ImageContent))
assert image_item.data == "ZmFrZWltYWdlZGF0YQ=="
def test_list_of_mixed_types_list(self):
"""Test that a list of mixed types, including a list as one of the elements, is converted correctly."""
content1 = TextContent(type="text", text="hello")
image_obj = Image(data=b"fakeimagedata")
basic_data = [{"a": 1}, {"b": 2}]
result = _convert_to_content([content1, image_obj, basic_data])
assert isinstance(result, list)
assert len(result) == 3
text_content_count = sum(isinstance(item, TextContent) for item in result)
image_content_count = sum(isinstance(item, ImageContent) for item in result)
assert text_content_count == 2
assert image_content_count == 1
text_item = next(item for item in result if isinstance(item, TextContent))
assert text_item.text == '[[{"a":1},{"b":2}]]'
image_item = next(item for item in result if isinstance(item, ImageContent))
assert image_item.data == "ZmFrZWltYWdlZGF0YQ=="
def test_list_of_mixed_types_with_audio(self):
"""Test that a list of mixed types including Audio is converted correctly."""
content1 = TextContent(type="text", text="hello")
audio_obj = Audio(data=b"fakeaudiodata")
basic_data = {"a": 1}
result = _convert_to_content([content1, audio_obj, basic_data])
assert isinstance(result, list)
assert len(result) == 3
text_content_count = sum(isinstance(item, TextContent) for item in result)
audio_content_count = sum(isinstance(item, AudioContent) for item in result)
assert text_content_count == 2
assert audio_content_count == 1
text_item = next(item for item in result if isinstance(item, TextContent))
assert text_item.text == '[{"a":1}]'
audio_item = next(item for item in result if isinstance(item, AudioContent))
assert audio_item.data == "ZmFrZWF1ZGlvZGF0YQ=="
def test_list_of_mixed_types_with_file(self):
"""Test that a list of mixed types including File is converted correctly."""
content1 = TextContent(type="text", text="hello")
file_obj = File(data=b"filedata", format="octet-stream")
basic_data = {"a": 1}
result = _convert_to_content([content1, file_obj, basic_data])
assert isinstance(result, list)
assert len(result) == 3
text_content_count = sum(isinstance(item, TextContent) for item in result)
embedded_content_count = sum(
isinstance(item, EmbeddedResource) and item.type == "resource"
for item in result
)
assert text_content_count == 2
assert embedded_content_count == 1
text_item = next(item for item in result if isinstance(item, TextContent))
assert text_item.text == '[{"a":1}]'
embedded_item = next(
item
for item in result
if isinstance(item, EmbeddedResource) and item.type == "resource"
)
resource = embedded_item.resource
assert resource.mimeType == "application/octet-stream"
# Check for blob attribute and its value
assert hasattr(resource, "blob")
assert getattr(resource, "blob") == "ZmlsZWRhdGE="
def test_empty_list(self):
"""Test that an empty list results in an empty list."""
result = _convert_to_content([])
assert isinstance(result, list)
assert len(result) == 0
def test_empty_dict(self):
"""Test that an empty dictionary is converted to TextContent."""
result = _convert_to_content({})
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], TextContent)
assert result[0].text == "{}"
def test_with_custom_serializer(self):
"""Test that a custom serializer is used for non-MCP types."""
def custom_serializer(data):
return f"Serialized: {data}"
result = _convert_to_content({"a": 1}, serializer=custom_serializer)
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], TextContent)
assert result[0].text == "Serialized: {'a': 1}"
def test_custom_serializer_error_fallback(self, caplog):
"""Test that if a custom serializer fails, it falls back to the default."""
def custom_serializer_that_fails(data):
raise ValueError("Serialization failed")
with caplog_for_fastmcp(caplog):
result = _convert_to_content(
{"a": 1}, serializer=custom_serializer_that_fails
)
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], TextContent)
# Should fall back to default serializer (pydantic_core.to_json)
assert json.loads(result[0].text) == {"a": 1}
assert "Error serializing tool result" in caplog.text
def test_process_as_single_item_flag(self):
"""Test that _process_as_single_item forces list to be treated as one item."""
result = _convert_to_content([1, "two", {"c": 3}], _process_as_single_item=True)
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], TextContent)
assert result[0].text == '[1,"two",{"c":3}]'
content1 = TextContent(type="text", text="hello")
result = _convert_to_content([1, content1], _process_as_single_item=True)
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], TextContent)
assert json.loads(result[0].text) == [
1,
{"type": "text", "text": "hello", "annotations": None, "_meta": None},
]
def test_single_element_list_preserves_structure(self):
"""Test that single-element lists preserve their list structure."""
# Test with a single integer
result = _convert_to_content([1])
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], TextContent)
assert result[0].text == "[1]" # Should be "[1]", not "1"
# Test with a single string
result = _convert_to_content(["hello"])
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], TextContent)
assert result[0].text == '["hello"]' # Should be ["hello"], not "hello"
# Test with a single dict
result = _convert_to_content([{"a": 1}])
assert isinstance(result, list)
assert len(result) == 1
assert isinstance(result[0], TextContent)
assert result[0].text == '[{"a":1}]' # Should be wrapped in a list
class TestAutomaticStructuredContent:
"""Tests for automatic structured content generation based on return types."""
async def test_dict_return_creates_structured_content_without_schema(self):
"""Test that dict returns automatically create structured content even without output schema."""
def get_user_data(user_id: str) -> dict:
return {"name": "Alice", "age": 30, "active": True}
# No explicit output schema provided
tool = Tool.from_function(get_user_data)
result = await tool.run({"user_id": "123"})
# Should have both content and structured content
assert len(result.content) == 1
assert isinstance(result.content[0], TextContent)
assert result.structured_content == {"name": "Alice", "age": 30, "active": True}
async def test_dataclass_return_creates_structured_content_without_schema(self):
"""Test that dataclass returns automatically create structured content even without output schema."""
@dataclass
class UserProfile:
name: str
age: int
email: str
def get_profile(user_id: str) -> UserProfile:
return UserProfile(name="Bob", age=25, email="bob@example.com")
# No explicit output schema, but dataclass should still create structured content
tool = Tool.from_function(get_profile, output_schema=None)
result = await tool.run({"user_id": "456"})
# Should have both content and structured content
assert len(result.content) == 1
assert isinstance(result.content[0], TextContent)
# Dataclass should serialize to dict
assert result.structured_content == {
"name": "Bob",
"age": 25,
"email": "bob@example.com",
}
async def test_pydantic_model_return_creates_structured_content_without_schema(
self,
):
"""Test that Pydantic model returns automatically create structured content even without output schema."""
class UserData(BaseModel):
username: str
score: int
verified: bool
def get_user_stats(user_id: str) -> UserData:
return UserData(username="charlie", score=100, verified=True)
# Explicitly set output schema to None to test automatic structured content
tool = Tool.from_function(get_user_stats, output_schema=None)
result = await tool.run({"user_id": "789"})
# Should have both content and structured content
assert len(result.content) == 1
assert isinstance(result.content[0], TextContent)
# Pydantic model should serialize to dict
assert result.structured_content == {
"username": "charlie",
"score": 100,
"verified": True,
}
async def test_int_return_no_structured_content_without_schema(self):
"""Test that int returns don't create structured content without output schema."""
def calculate_sum(a: int, b: int):
"""No return annotation."""
return a + b
# No output schema
tool = Tool.from_function(calculate_sum)
result = await tool.run({"a": 5, "b": 3})
# Should only have content, no structured content
assert len(result.content) == 1
assert isinstance(result.content[0], TextContent)
assert result.content[0].text == "8"
assert result.structured_content is None
async def test_str_return_no_structured_content_without_schema(self):
"""Test that str returns don't create structured content without output schema."""
def get_greeting(name: str):
"""No return annotation."""
return f"Hello, {name}!"
# No output schema
tool = Tool.from_function(get_greeting)
result = await tool.run({"name": "World"})
# Should only have content, no structured content
assert len(result.content) == 1
assert isinstance(result.content[0], TextContent)
assert result.content[0].text == "Hello, World!"
assert result.structured_content is None
async def test_list_return_no_structured_content_without_schema(self):
"""Test that list returns don't create structured content without output schema."""
def get_numbers():
"""No return annotation."""
return [1, 2, 3, 4, 5]
# No output schema
tool = Tool.from_function(get_numbers)
result = await tool.run({})
# Should only have content, no structured content
assert len(result.content) == 1
assert isinstance(result.content[0], TextContent)
assert result.structured_content is None
async def test_int_return_with_schema_creates_structured_content(self):
"""Test that int returns DO create structured content when there's an output schema."""
def calculate_sum(a: int, b: int) -> int:
"""With return annotation."""
return a + b
# Output schema should be auto-generated from annotation
tool = Tool.from_function(calculate_sum)
assert tool.output_schema is not None
result = await tool.run({"a": 5, "b": 3})
# Should have both content and structured content
assert len(result.content) == 1
assert isinstance(result.content[0], TextContent)
assert result.content[0].text == "8"
assert result.structured_content == {"result": 8}
async def test_client_automatic_deserialization_with_dict_result(self):
"""Test that clients automatically deserialize dict results from structured content."""
from fastmcp import FastMCP
from fastmcp.client import Client
mcp = FastMCP()
@mcp.tool
def get_user_info(user_id: str) -> dict:
return {"name": "Alice", "age": 30, "active": True}
async with Client(mcp) as client:
result = await client.call_tool("get_user_info", {"user_id": "123"})
# Client should provide the deserialized data
assert result.data == {"name": "Alice", "age": 30, "active": True}
assert result.structured_content == {
"name": "Alice",
"age": 30,
"active": True,
}
assert len(result.content) == 1
async def test_client_automatic_deserialization_with_dataclass_result(self):
"""Test that clients automatically deserialize dataclass results from structured content."""
from fastmcp import FastMCP
from fastmcp.client import Client
mcp = FastMCP()
@dataclass
class UserProfile:
name: str
age: int
verified: bool
@mcp.tool
def get_profile(user_id: str) -> UserProfile:
return UserProfile(name="Bob", age=25, verified=True)
async with Client(mcp) as client:
result = await client.call_tool("get_profile", {"user_id": "456"})
# Client should deserialize back to a dataclass (type name preserved with new compression)
assert result.data.__class__.__name__ == "UserProfile"
assert result.data.name == "Bob"
assert result.data.age == 25
assert result.data.verified is True
class TestUnionReturnTypes:
"""Tests for tools with union return types."""
async def test_dataclass_union_string_works(self):
"""Test that union of dataclass and string works correctly."""
@dataclass
class Data:
value: int
def get_data(return_error: bool) -> Data | str:
if return_error:
return "error occurred"
return Data(value=42)
tool = Tool.from_function(get_data)
# Test returning dataclass
result1 = await tool.run({"return_error": False})
assert result1.structured_content == {"result": {"value": 42}}
# Test returning string
result2 = await tool.run({"return_error": True})
assert result2.structured_content == {"result": "error occurred"}
class TestSerializationAlias:
"""Tests for Pydantic field serialization alias support in tool output schemas."""
def test_output_schema_respects_serialization_alias(self):
"""Test that Tool.from_function generates output schema using serialization alias."""
from pydantic import AliasChoices, BaseModel, Field
class Component(BaseModel):
"""Model with multiple validation aliases but specific serialization alias."""
component_id: str = Field(
validation_alias=AliasChoices("id", "componentId"),
serialization_alias="componentId",
description="The ID of the component",
)
async def get_component(
component_id: str,
) -> Annotated[Component, Field(description="The component.")]:
# API returns data with 'id' field
api_data = {"id": component_id}
return Component.model_validate(api_data)
tool = Tool.from_function(get_component, name="get-component")
# The output schema should use the serialization alias 'componentId'
# not the first validation alias 'id'
assert tool.output_schema is not None
# Check the wrapped result schema
assert "properties" in tool.output_schema
assert "result" in tool.output_schema["properties"]
assert "$defs" in tool.output_schema
# Find the Component definition
component_def = list(tool.output_schema["$defs"].values())[0]
# Should have 'componentId' not 'id' in properties
assert "componentId" in component_def["properties"]
assert "id" not in component_def["properties"]
# Should require 'componentId' not 'id'
assert "componentId" in component_def["required"]
assert "id" not in component_def.get("required", [])
async def test_tool_execution_with_serialization_alias(self):
"""Test that tool execution works correctly with serialization aliases."""
from pydantic import AliasChoices, BaseModel, Field
from fastmcp import Client, FastMCP
class Component(BaseModel):
"""Model with multiple validation aliases but specific serialization alias."""
component_id: str = Field(
validation_alias=AliasChoices("id", "componentId"),
serialization_alias="componentId",
description="The ID of the component",
)
mcp = FastMCP("TestServer")
@mcp.tool
async def get_component(
component_id: str,
) -> Annotated[Component, Field(description="The component.")]:
# API returns data with 'id' field
api_data = {"id": component_id}
return Component.model_validate(api_data)
async with Client(mcp) as client:
# Execute the tool - this should work without validation errors
result = await client.call_tool(
"get_component", {"component_id": "test123"}
)
# The result should contain the serialized form with 'componentId'
assert result.structured_content is not None
assert result.structured_content["result"]["componentId"] == "test123"
assert "id" not in result.structured_content["result"]
class TestToolTitle:
"""Tests for tool title functionality."""
def test_tool_with_title(self):
"""Test that tools can have titles and they appear in MCP conversion."""
def calculate(x: int, y: int) -> int:
"""Calculate the sum of two numbers."""
return x + y
tool = Tool.from_function(
calculate,
name="calc",
title="Advanced Calculator Tool",
description="Custom description",
)
assert tool.name == "calc"
assert tool.title == "Advanced Calculator Tool"
assert tool.description == "Custom description"
# Test MCP conversion includes title
mcp_tool = tool.to_mcp_tool()
assert mcp_tool.name == "calc"
assert (
hasattr(mcp_tool, "title") and mcp_tool.title == "Advanced Calculator Tool"
)
def test_tool_without_title(self):
"""Test that tools without titles use name as display name."""
def multiply(a: int, b: int) -> int:
return a * b
tool = Tool.from_function(multiply)
assert tool.name == "multiply"
assert tool.title is None
# Test MCP conversion doesn't include title when None
mcp_tool = tool.to_mcp_tool()
assert mcp_tool.name == "multiply"
assert not hasattr(mcp_tool, "title") or mcp_tool.title is None
def test_tool_title_priority(self):
"""Test that explicit title takes priority over annotations.title."""
from mcp.types import ToolAnnotations
def divide(x: int, y: int) -> float:
"""Divide two numbers."""
return x / y
# Test with both explicit title and annotations.title
annotations = ToolAnnotations(title="Annotation Title")
tool = Tool.from_function(
divide,
name="div",
title="Explicit Title",
annotations=annotations,
)
assert tool.title == "Explicit Title"
assert tool.annotations is not None
assert tool.annotations.title == "Annotation Title"
# Explicit title should take priority
mcp_tool = tool.to_mcp_tool()
assert mcp_tool.title == "Explicit Title"
def test_tool_annotations_title_fallback(self):
"""Test that annotations.title is used when no explicit title is provided."""
from mcp.types import ToolAnnotations
def modulo(x: int, y: int) -> int:
"""Get modulo of two numbers."""
return x % y
# Test with only annotations.title (no explicit title)
annotations = ToolAnnotations(title="Annotation Title")
tool = Tool.from_function(
modulo,
name="mod",
annotations=annotations,
)
assert tool.title is None
assert tool.annotations is not None
assert tool.annotations.title == "Annotation Title"
# Should fall back to annotations.title
mcp_tool = tool.to_mcp_tool()
assert mcp_tool.title == "Annotation Title"