feat: Add structured output support for tool functions (#993)

tests/server/fastmcp/test_func_metadata.py

@@ -1,4 +1,5 @@
-from typing import Annotated
+from dataclasses import dataclass
+from typing import Annotated, Any, TypedDict
 
 import annotated_types
 import pytest
@@ -193,6 +194,50 @@ def test_skip_names():
     assert model.also_keep == 2.5  # type: ignore
 
 
+def test_structured_output_dict_str_types():
+    """Test that dict[str, T] types are handled without wrapping."""
+
+    # Test dict[str, Any]
+    def func_dict_any() -> dict[str, Any]:
+        return {"a": 1, "b": "hello", "c": [1, 2, 3]}
+
+    meta = func_metadata(func_dict_any)
+    assert meta.output_schema == {
+        "type": "object",
+        "title": "func_dict_anyDictOutput",
+    }
+
+    # Test dict[str, str]
+    def func_dict_str() -> dict[str, str]:
+        return {"name": "John", "city": "NYC"}
+
+    meta = func_metadata(func_dict_str)
+    assert meta.output_schema == {
+        "type": "object",
+        "additionalProperties": {"type": "string"},
+        "title": "func_dict_strDictOutput",
+    }
+
+    # Test dict[str, list[int]]
+    def func_dict_list() -> dict[str, list[int]]:
+        return {"nums": [1, 2, 3], "more": [4, 5, 6]}
+
+    meta = func_metadata(func_dict_list)
+    assert meta.output_schema == {
+        "type": "object",
+        "additionalProperties": {"type": "array", "items": {"type": "integer"}},
+        "title": "func_dict_listDictOutput",
+    }
+
+    # Test dict[int, str] - should be wrapped since key is not str
+    def func_dict_int_key() -> dict[int, str]:
+        return {1: "a", 2: "b"}
+
+    meta = func_metadata(func_dict_int_key)
+    assert meta.output_schema is not None
+    assert "result" in meta.output_schema["properties"]
+
+
 @pytest.mark.anyio
 async def test_lambda_function():
     """Test lambda function schema and validation"""
@@ -408,3 +453,390 @@ def test_str_vs_int():
     result = meta.pre_parse_json({"a": "123", "b": 123})
     assert result["a"] == "123"
     assert result["b"] == 123
+
+
+# Tests for structured output functionality
+
+
+def test_structured_output_requires_return_annotation():
+    """Test that structured_output=True requires a return annotation"""
+    from mcp.server.fastmcp.exceptions import InvalidSignature
+
+    def func_no_annotation():
+        return "hello"
+
+    def func_none_annotation() -> None:
+        return None
+
+    with pytest.raises(InvalidSignature) as exc_info:
+        func_metadata(func_no_annotation, structured_output=True)
+    assert "return annotation required" in str(exc_info.value)
+
+    # None annotation should work
+    meta = func_metadata(func_none_annotation)
+    assert meta.output_schema == {
+        "type": "object",
+        "properties": {"result": {"title": "Result", "type": "null"}},
+        "required": ["result"],
+        "title": "func_none_annotationOutput",
+    }
+
+
+def test_structured_output_basemodel():
+    """Test structured output with BaseModel return types"""
+
+    class PersonModel(BaseModel):
+        name: str
+        age: int
+        email: str | None = None
+
+    def func_returning_person() -> PersonModel:
+        return PersonModel(name="Alice", age=30)
+
+    meta = func_metadata(func_returning_person)
+    assert meta.output_schema == {
+        "type": "object",
+        "properties": {
+            "name": {"title": "Name", "type": "string"},
+            "age": {"title": "Age", "type": "integer"},
+            "email": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": None, "title": "Email"},
+        },
+        "required": ["name", "age"],
+        "title": "PersonModel",
+    }
+
+
+def test_structured_output_primitives():
+    """Test structured output with primitive return types"""
+
+    def func_str() -> str:
+        return "hello"
+
+    def func_int() -> int:
+        return 42
+
+    def func_float() -> float:
+        return 3.14
+
+    def func_bool() -> bool:
+        return True
+
+    def func_bytes() -> bytes:
+        return b"data"
+
+    # Test string
+    meta = func_metadata(func_str)
+    assert meta.output_schema == {
+        "type": "object",
+        "properties": {"result": {"title": "Result", "type": "string"}},
+        "required": ["result"],
+        "title": "func_strOutput",
+    }
+
+    # Test int
+    meta = func_metadata(func_int)
+    assert meta.output_schema == {
+        "type": "object",
+        "properties": {"result": {"title": "Result", "type": "integer"}},
+        "required": ["result"],
+        "title": "func_intOutput",
+    }
+
+    # Test float
+    meta = func_metadata(func_float)
+    assert meta.output_schema == {
+        "type": "object",
+        "properties": {"result": {"title": "Result", "type": "number"}},
+        "required": ["result"],
+        "title": "func_floatOutput",
+    }
+
+    # Test bool
+    meta = func_metadata(func_bool)
+    assert meta.output_schema == {
+        "type": "object",
+        "properties": {"result": {"title": "Result", "type": "boolean"}},
+        "required": ["result"],
+        "title": "func_boolOutput",
+    }
+
+    # Test bytes
+    meta = func_metadata(func_bytes)
+    assert meta.output_schema == {
+        "type": "object",
+        "properties": {"result": {"title": "Result", "type": "string", "format": "binary"}},
+        "required": ["result"],
+        "title": "func_bytesOutput",
+    }
+
+
+def test_structured_output_generic_types():
+    """Test structured output with generic types (list, dict, Union, etc.)"""
+
+    def func_list_str() -> list[str]:
+        return ["a", "b", "c"]
+
+    def func_dict_str_int() -> dict[str, int]:
+        return {"a": 1, "b": 2}
+
+    def func_union() -> str | int:
+        return "hello"
+
+    def func_optional() -> str | None:
+        return None
+
+    # Test list
+    meta = func_metadata(func_list_str)
+    assert meta.output_schema == {
+        "type": "object",
+        "properties": {"result": {"title": "Result", "type": "array", "items": {"type": "string"}}},
+        "required": ["result"],
+        "title": "func_list_strOutput",
+    }
+
+    # Test dict[str, int] - should NOT be wrapped
+    meta = func_metadata(func_dict_str_int)
+    assert meta.output_schema == {
+        "type": "object",
+        "additionalProperties": {"type": "integer"},
+        "title": "func_dict_str_intDictOutput",
+    }
+
+    # Test Union
+    meta = func_metadata(func_union)
+    assert meta.output_schema == {
+        "type": "object",
+        "properties": {"result": {"title": "Result", "anyOf": [{"type": "string"}, {"type": "integer"}]}},
+        "required": ["result"],
+        "title": "func_unionOutput",
+    }
+
+    # Test Optional
+    meta = func_metadata(func_optional)
+    assert meta.output_schema == {
+        "type": "object",
+        "properties": {"result": {"title": "Result", "anyOf": [{"type": "string"}, {"type": "null"}]}},
+        "required": ["result"],
+        "title": "func_optionalOutput",
+    }
+
+
+def test_structured_output_dataclass():
+    """Test structured output with dataclass return types"""
+
+    @dataclass
+    class PersonDataClass:
+        name: str
+        age: int
+        email: str | None = None
+        tags: list[str] | None = None
+
+    def func_returning_dataclass() -> PersonDataClass:
+        return PersonDataClass(name="Bob", age=25)
+
+    meta = func_metadata(func_returning_dataclass)
+    assert meta.output_schema == {
+        "type": "object",
+        "properties": {
+            "name": {"title": "Name", "type": "string"},
+            "age": {"title": "Age", "type": "integer"},
+            "email": {"anyOf": [{"type": "string"}, {"type": "null"}], "default": None, "title": "Email"},
+            "tags": {
+                "anyOf": [{"items": {"type": "string"}, "type": "array"}, {"type": "null"}],
+                "default": None,
+                "title": "Tags",
+            },
+        },
+        "required": ["name", "age"],
+        "title": "PersonDataClass",
+    }
+
+
+def test_structured_output_typeddict():
+    """Test structured output with TypedDict return types"""
+
+    class PersonTypedDictOptional(TypedDict, total=False):
+        name: str
+        age: int
+
+    def func_returning_typeddict_optional() -> PersonTypedDictOptional:
+        return {"name": "Dave"}  # Only returning one field to test partial dict
+
+    meta = func_metadata(func_returning_typeddict_optional)
+    assert meta.output_schema == {
+        "type": "object",
+        "properties": {
+            "name": {"title": "Name", "type": "string", "default": None},
+            "age": {"title": "Age", "type": "integer", "default": None},
+        },
+        "title": "PersonTypedDictOptional",
+    }
+
+    # Test with total=True (all required)
+    class PersonTypedDictRequired(TypedDict):
+        name: str
+        age: int
+        email: str | None
+
+    def func_returning_typeddict_required() -> PersonTypedDictRequired:
+        return {"name": "Eve", "age": 40, "email": None}  # Testing None value
+
+    meta = func_metadata(func_returning_typeddict_required)
+    assert meta.output_schema == {
+        "type": "object",
+        "properties": {
+            "name": {"title": "Name", "type": "string"},
+            "age": {"title": "Age", "type": "integer"},
+            "email": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Email"},
+        },
+        "required": ["name", "age", "email"],
+        "title": "PersonTypedDictRequired",
+    }
+
+
+def test_structured_output_ordinary_class():
+    """Test structured output with ordinary annotated classes"""
+
+    class PersonClass:
+        name: str
+        age: int
+        email: str | None
+
+        def __init__(self, name: str, age: int, email: str | None = None):
+            self.name = name
+            self.age = age
+            self.email = email
+
+    def func_returning_class() -> PersonClass:
+        return PersonClass("Helen", 55)
+
+    meta = func_metadata(func_returning_class)
+    assert meta.output_schema == {
+        "type": "object",
+        "properties": {
+            "name": {"title": "Name", "type": "string"},
+            "age": {"title": "Age", "type": "integer"},
+            "email": {"anyOf": [{"type": "string"}, {"type": "null"}], "title": "Email"},
+        },
+        "required": ["name", "age", "email"],
+        "title": "PersonClass",
+    }
+
+
+def test_unstructured_output_unannotated_class():
+    # Test with class that has no annotations
+    class UnannotatedClass:
+        def __init__(self, x, y):
+            self.x = x
+            self.y = y
+
+    def func_returning_unannotated() -> UnannotatedClass:
+        return UnannotatedClass(1, 2)
+
+    meta = func_metadata(func_returning_unannotated)
+    assert meta.output_schema is None
+
+
+def test_structured_output_with_field_descriptions():
+    """Test that Field descriptions are preserved in structured output"""
+
+    class ModelWithDescriptions(BaseModel):
+        name: Annotated[str, Field(description="The person's full name")]
+        age: Annotated[int, Field(description="Age in years", ge=0, le=150)]
+
+    def func_with_descriptions() -> ModelWithDescriptions:
+        return ModelWithDescriptions(name="Ian", age=60)
+
+    meta = func_metadata(func_with_descriptions)
+    assert meta.output_schema == {
+        "type": "object",
+        "properties": {
+            "name": {"title": "Name", "type": "string", "description": "The person's full name"},
+            "age": {"title": "Age", "type": "integer", "description": "Age in years", "minimum": 0, "maximum": 150},
+        },
+        "required": ["name", "age"],
+        "title": "ModelWithDescriptions",
+    }
+
+
+def test_structured_output_nested_models():
+    """Test structured output with nested models"""
+
+    class Address(BaseModel):
+        street: str
+        city: str
+        zipcode: str
+
+    class PersonWithAddress(BaseModel):
+        name: str
+        address: Address
+
+    def func_nested() -> PersonWithAddress:
+        return PersonWithAddress(name="Jack", address=Address(street="123 Main St", city="Anytown", zipcode="12345"))
+
+    meta = func_metadata(func_nested)
+    assert meta.output_schema == {
+        "type": "object",
+        "$defs": {
+            "Address": {
+                "type": "object",
+                "properties": {
+                    "street": {"title": "Street", "type": "string"},
+                    "city": {"title": "City", "type": "string"},
+                    "zipcode": {"title": "Zipcode", "type": "string"},
+                },
+                "required": ["street", "city", "zipcode"],
+                "title": "Address",
+            }
+        },
+        "properties": {
+            "name": {"title": "Name", "type": "string"},
+            "address": {"$ref": "#/$defs/Address"},
+        },
+        "required": ["name", "address"],
+        "title": "PersonWithAddress",
+    }
+
+
+def test_structured_output_unserializable_type_error():
+    """Test error when structured_output=True is used with unserializable types"""
+    from typing import NamedTuple
+
+    from mcp.server.fastmcp.exceptions import InvalidSignature
+
+    # Test with a class that has non-serializable default values
+    class ConfigWithCallable:
+        name: str
+        # Callable defaults are not JSON serializable and will trigger Pydantic warnings
+        callback: Any = lambda x: x * 2
+
+    def func_returning_config_with_callable() -> ConfigWithCallable:
+        return ConfigWithCallable()
+
+    # Should work without structured_output=True (returns None for output_schema)
+    meta = func_metadata(func_returning_config_with_callable)
+    assert meta.output_schema is None
+
+    # Should raise error with structured_output=True
+    with pytest.raises(InvalidSignature) as exc_info:
+        func_metadata(func_returning_config_with_callable, structured_output=True)
+    assert "is not serializable for structured output" in str(exc_info.value)
+    assert "ConfigWithCallable" in str(exc_info.value)
+
+    # Also test with NamedTuple for good measure
+    class Point(NamedTuple):
+        x: int
+        y: int
+
+    def func_returning_namedtuple() -> Point:
+        return Point(1, 2)
+
+    # Should work without structured_output=True (returns None for output_schema)
+    meta = func_metadata(func_returning_namedtuple)
+    assert meta.output_schema is None
+
+    # Should raise error with structured_output=True
+    with pytest.raises(InvalidSignature) as exc_info:
+        func_metadata(func_returning_namedtuple, structured_output=True)
+    assert "is not serializable for structured output" in str(exc_info.value)
+    assert "Point" in str(exc_info.value)

tests/server/fastmcp/test_server.py

@@ -1,10 +1,10 @@
 import base64
 from pathlib import Path
-from typing import TYPE_CHECKING
+from typing import TYPE_CHECKING, Any
 from unittest.mock import patch
 
 import pytest
-from pydantic import AnyUrl
+from pydantic import AnyUrl, BaseModel
 from starlette.routing import Mount, Route
 
 from mcp.server.fastmcp import Context, FastMCP
@@ -274,6 +274,9 @@ class TestServerTools:
             content = result.content[0]
             assert isinstance(content, TextContent)
             assert content.text == "3"
+            # Check structured content - int return type should have structured output
+            assert result.structuredContent is not None
+            assert result.structuredContent == {"result": 3}
 
     @pytest.mark.anyio
     async def test_tool_image_helper(self, tmp_path: Path):
@@ -293,6 +296,8 @@ class TestServerTools:
             # Verify base64 encoding
             decoded = base64.b64decode(content.data)
             assert decoded == b"fake png data"
+            # Check structured content - Image return type should NOT have structured output
+            assert result.structuredContent is None
 
     @pytest.mark.anyio
     async def test_tool_mixed_content(self):
@@ -310,6 +315,20 @@ class TestServerTools:
             assert isinstance(content3, AudioContent)
             assert content3.mimeType == "audio/wav"
             assert content3.data == "def"
+            assert result.structuredContent is not None
+            assert "result" in result.structuredContent
+            structured_result = result.structuredContent["result"]
+            assert len(structured_result) == 3
+
+            expected_content = [
+                {"type": "text", "text": "Hello"},
+                {"type": "image", "data": "abc", "mimeType": "image/png"},
+                {"type": "audio", "data": "def", "mimeType": "audio/wav"},
+            ]
+
+            for i, expected in enumerate(expected_content):
+                for key, value in expected.items():
+                    assert structured_result[i][key] == value
 
     @pytest.mark.anyio
     async def test_tool_mixed_list_with_image(self, tmp_path: Path):
@@ -349,6 +368,169 @@ class TestServerTools:
             content4 = result.content[3]
             assert isinstance(content4, TextContent)
             assert content4.text == "direct content"
+            # Check structured content - untyped list with Image objects should NOT have structured output
+            assert result.structuredContent is None
+
+    @pytest.mark.anyio
+    async def test_tool_structured_output_basemodel(self):
+        """Test tool with structured output returning BaseModel"""
+
+        class UserOutput(BaseModel):
+            name: str
+            age: int
+            active: bool = True
+
+        def get_user(user_id: int) -> UserOutput:
+            """Get user by ID"""
+            return UserOutput(name="John Doe", age=30)
+
+        mcp = FastMCP()
+        mcp.add_tool(get_user)
+
+        async with client_session(mcp._mcp_server) as client:
+            # Check that the tool has outputSchema
+            tools = await client.list_tools()
+            tool = next(t for t in tools.tools if t.name == "get_user")
+            assert tool.outputSchema is not None
+            assert tool.outputSchema["type"] == "object"
+            assert "name" in tool.outputSchema["properties"]
+            assert "age" in tool.outputSchema["properties"]
+
+            # Call the tool and check structured output
+            result = await client.call_tool("get_user", {"user_id": 123})
+            assert result.isError is False
+            assert result.structuredContent is not None
+            assert result.structuredContent == {"name": "John Doe", "age": 30, "active": True}
+            # Content should be JSON serialized version
+            assert len(result.content) == 1
+            assert isinstance(result.content[0], TextContent)
+            assert '"name": "John Doe"' in result.content[0].text
+
+    @pytest.mark.anyio
+    async def test_tool_structured_output_primitive(self):
+        """Test tool with structured output returning primitive type"""
+
+        def calculate_sum(a: int, b: int) -> int:
+            """Add two numbers"""
+            return a + b
+
+        mcp = FastMCP()
+        mcp.add_tool(calculate_sum)
+
+        async with client_session(mcp._mcp_server) as client:
+            # Check that the tool has outputSchema
+            tools = await client.list_tools()
+            tool = next(t for t in tools.tools if t.name == "calculate_sum")
+            assert tool.outputSchema is not None
+            # Primitive types are wrapped
+            assert tool.outputSchema["type"] == "object"
+            assert "result" in tool.outputSchema["properties"]
+            assert tool.outputSchema["properties"]["result"]["type"] == "integer"
+
+            # Call the tool
+            result = await client.call_tool("calculate_sum", {"a": 5, "b": 7})
+            assert result.isError is False
+            assert result.structuredContent is not None
+            assert result.structuredContent == {"result": 12}
+
+    @pytest.mark.anyio
+    async def test_tool_structured_output_list(self):
+        """Test tool with structured output returning list"""
+
+        def get_numbers() -> list[int]:
+            """Get a list of numbers"""
+            return [1, 2, 3, 4, 5]
+
+        mcp = FastMCP()
+        mcp.add_tool(get_numbers)
+
+        async with client_session(mcp._mcp_server) as client:
+            result = await client.call_tool("get_numbers", {})
+            assert result.isError is False
+            assert result.structuredContent is not None
+            assert result.structuredContent == {"result": [1, 2, 3, 4, 5]}
+
+    @pytest.mark.anyio
+    async def test_tool_structured_output_server_side_validation_error(self):
+        """Test that server-side validation errors are handled properly"""
+
+        def get_numbers() -> list[int]:
+            return [1, 2, 3, 4, [5]]  # type: ignore
+
+        mcp = FastMCP()
+        mcp.add_tool(get_numbers)
+
+        async with client_session(mcp._mcp_server) as client:
+            result = await client.call_tool("get_numbers", {})
+            assert result.isError is True
+            assert result.structuredContent is None
+            assert len(result.content) == 1
+            assert isinstance(result.content[0], TextContent)
+
+    @pytest.mark.anyio
+    async def test_tool_structured_output_dict_str_any(self):
+        """Test tool with dict[str, Any] structured output"""
+
+        def get_metadata() -> dict[str, Any]:
+            """Get metadata dictionary"""
+            return {
+                "version": "1.0.0",
+                "enabled": True,
+                "count": 42,
+                "tags": ["production", "stable"],
+                "config": {"nested": {"value": 123}},
+            }
+
+        mcp = FastMCP()
+        mcp.add_tool(get_metadata)
+
+        async with client_session(mcp._mcp_server) as client:
+            # Check schema
+            tools = await client.list_tools()
+            tool = next(t for t in tools.tools if t.name == "get_metadata")
+            assert tool.outputSchema is not None
+            assert tool.outputSchema["type"] == "object"
+            # dict[str, Any] should have minimal schema
+            assert (
+                "additionalProperties" not in tool.outputSchema or tool.outputSchema.get("additionalProperties") is True
+            )
+
+            # Call tool
+            result = await client.call_tool("get_metadata", {})
+            assert result.isError is False
+            assert result.structuredContent is not None
+            expected = {
+                "version": "1.0.0",
+                "enabled": True,
+                "count": 42,
+                "tags": ["production", "stable"],
+                "config": {"nested": {"value": 123}},
+            }
+            assert result.structuredContent == expected
+
+    @pytest.mark.anyio
+    async def test_tool_structured_output_dict_str_typed(self):
+        """Test tool with dict[str, T] structured output for specific T"""
+
+        def get_settings() -> dict[str, str]:
+            """Get settings as string dictionary"""
+            return {"theme": "dark", "language": "en", "timezone": "UTC"}
+
+        mcp = FastMCP()
+        mcp.add_tool(get_settings)
+
+        async with client_session(mcp._mcp_server) as client:
+            # Check schema
+            tools = await client.list_tools()
+            tool = next(t for t in tools.tools if t.name == "get_settings")
+            assert tool.outputSchema is not None
+            assert tool.outputSchema["type"] == "object"
+            assert tool.outputSchema["additionalProperties"]["type"] == "string"
+
+            # Call tool
+            result = await client.call_tool("get_settings", {})
+            assert result.isError is False
+            assert result.structuredContent == {"theme": "dark", "language": "en", "timezone": "UTC"}
 
 
 class TestServerResources:

tests/server/fastmcp/test_tool_manager.py

@@ -1,5 +1,7 @@
 import json
 import logging
+from dataclasses import dataclass
+from typing import Any, TypedDict
 
 import pytest
 from pydantic import BaseModel
@@ -10,7 +12,7 @@ from mcp.server.fastmcp.tools import Tool, ToolManager
 from mcp.server.fastmcp.utilities.func_metadata import ArgModelBase, FuncMetadata
 from mcp.server.session import ServerSessionT
 from mcp.shared.context import LifespanContextT, RequestT
-from mcp.types import ToolAnnotations
+from mcp.types import TextContent, ToolAnnotations
 
 
 class TestAddTools:
@@ -450,3 +452,184 @@ class TestToolAnnotations:
         assert tools[0].annotations is not None
         assert tools[0].annotations.title == "Echo Tool"
         assert tools[0].annotations.readOnlyHint is True
+
+
+class TestStructuredOutput:
+    """Test structured output functionality in tools."""
+
+    @pytest.mark.anyio
+    async def test_tool_with_basemodel_output(self):
+        """Test tool with BaseModel return type."""
+
+        class UserOutput(BaseModel):
+            name: str
+            age: int
+
+        def get_user(user_id: int) -> UserOutput:
+            """Get user by ID."""
+            return UserOutput(name="John", age=30)
+
+        manager = ToolManager()
+        manager.add_tool(get_user)
+        result = await manager.call_tool("get_user", {"user_id": 1}, convert_result=True)
+        # don't test unstructured output here, just the structured conversion
+        assert len(result) == 2 and result[1] == {"name": "John", "age": 30}
+
+    @pytest.mark.anyio
+    async def test_tool_with_primitive_output(self):
+        """Test tool with primitive return type."""
+
+        def double_number(n: int) -> int:
+            """Double a number."""
+            return 10
+
+        manager = ToolManager()
+        manager.add_tool(double_number)
+        result = await manager.call_tool("double_number", {"n": 5})
+        assert result == 10
+        result = await manager.call_tool("double_number", {"n": 5}, convert_result=True)
+        assert isinstance(result[0][0], TextContent) and result[1] == {"result": 10}
+
+    @pytest.mark.anyio
+    async def test_tool_with_typeddict_output(self):
+        """Test tool with TypedDict return type."""
+
+        class UserDict(TypedDict):
+            name: str
+            age: int
+
+        expected_output = {"name": "Alice", "age": 25}
+
+        def get_user_dict(user_id: int) -> UserDict:
+            """Get user as dict."""
+            return UserDict(name="Alice", age=25)
+
+        manager = ToolManager()
+        manager.add_tool(get_user_dict)
+        result = await manager.call_tool("get_user_dict", {"user_id": 1})
+        assert result == expected_output
+
+    @pytest.mark.anyio
+    async def test_tool_with_dataclass_output(self):
+        """Test tool with dataclass return type."""
+
+        @dataclass
+        class Person:
+            name: str
+            age: int
+
+        expected_output = {"name": "Bob", "age": 40}
+
+        def get_person() -> Person:
+            """Get a person."""
+            return Person("Bob", 40)
+
+        manager = ToolManager()
+        manager.add_tool(get_person)
+        result = await manager.call_tool("get_person", {}, convert_result=True)
+        # don't test unstructured output here, just the structured conversion
+        assert len(result) == 2 and result[1] == expected_output
+
+    @pytest.mark.anyio
+    async def test_tool_with_list_output(self):
+        """Test tool with list return type."""
+
+        expected_list = [1, 2, 3, 4, 5]
+        expected_output = {"result": expected_list}
+
+        def get_numbers() -> list[int]:
+            """Get a list of numbers."""
+            return expected_list
+
+        manager = ToolManager()
+        manager.add_tool(get_numbers)
+        result = await manager.call_tool("get_numbers", {})
+        assert result == expected_list
+        result = await manager.call_tool("get_numbers", {}, convert_result=True)
+        assert isinstance(result[0][0], TextContent) and result[1] == expected_output
+
+    @pytest.mark.anyio
+    async def test_tool_without_structured_output(self):
+        """Test that tools work normally when structured_output=False."""
+
+        def get_dict() -> dict:
+            """Get a dict."""
+            return {"key": "value"}
+
+        manager = ToolManager()
+        manager.add_tool(get_dict, structured_output=False)
+        result = await manager.call_tool("get_dict", {})
+        assert isinstance(result, dict)
+        assert result == {"key": "value"}
+
+    def test_tool_output_schema_property(self):
+        """Test that Tool.output_schema property works correctly."""
+
+        class UserOutput(BaseModel):
+            name: str
+            age: int
+
+        def get_user() -> UserOutput:
+            return UserOutput(name="Test", age=25)
+
+        manager = ToolManager()
+        tool = manager.add_tool(get_user)
+
+        # Test that output_schema is populated
+        expected_schema = {
+            "properties": {"name": {"type": "string", "title": "Name"}, "age": {"type": "integer", "title": "Age"}},
+            "required": ["name", "age"],
+            "title": "UserOutput",
+            "type": "object",
+        }
+        assert tool.output_schema == expected_schema
+
+    @pytest.mark.anyio
+    async def test_tool_with_dict_str_any_output(self):
+        """Test tool with dict[str, Any] return type."""
+
+        def get_config() -> dict[str, Any]:
+            """Get configuration"""
+            return {"debug": True, "port": 8080, "features": ["auth", "logging"]}
+
+        manager = ToolManager()
+        tool = manager.add_tool(get_config)
+
+        # Check output schema
+        assert tool.output_schema is not None
+        assert tool.output_schema["type"] == "object"
+        assert "properties" not in tool.output_schema  # dict[str, Any] has no constraints
+
+        # Test raw result
+        result = await manager.call_tool("get_config", {})
+        expected = {"debug": True, "port": 8080, "features": ["auth", "logging"]}
+        assert result == expected
+
+        # Test converted result
+        result = await manager.call_tool("get_config", {})
+        assert result == expected
+
+    @pytest.mark.anyio
+    async def test_tool_with_dict_str_typed_output(self):
+        """Test tool with dict[str, T] return type for specific T."""
+
+        def get_scores() -> dict[str, int]:
+            """Get player scores"""
+            return {"alice": 100, "bob": 85, "charlie": 92}
+
+        manager = ToolManager()
+        tool = manager.add_tool(get_scores)
+
+        # Check output schema
+        assert tool.output_schema is not None
+        assert tool.output_schema["type"] == "object"
+        assert tool.output_schema["additionalProperties"]["type"] == "integer"
+
+        # Test raw result
+        result = await manager.call_tool("get_scores", {})
+        expected = {"alice": 100, "bob": 85, "charlie": 92}
+        assert result == expected
+
+        # Test converted result
+        result = await manager.call_tool("get_scores", {})
+        assert result == expected