Repository: jlowin/fastmcp

Issue:
Bug: Unsuitable type convert in `FuncMetadata.pre_parse_json`
### Description

The function tries to convert `str` into JSON without validate if it is suitable for the type annotation. This will cause unintended type converting.

For example:

```python
@mcp.tool()
def foo(bar: str):
    return bar
```

Then calling `foo("{'key': 5}")` in MCP will raise `TypeError` since it converts the `str` into `dict`.

### Example Code

```Python

```

### Version Information

```Text
FastMCP version:                                       2.2.3
MCP version:                                           1.6.0
Python version:                                       3.12.3
Platform:                          Windows-11-10.0.26100-SP0
FastMCP root path: C:\Users\cutek\Documents\Code\fastmcp\src
```

### Additional Context

_No response_

Discussion:

Solution patch:
diff --git a/README.md b/README.md
index d0b83eb..31275b4 100644
--- a/README.md
+++ b/README.md
@@ -112,7 +112,7 @@ FastMCP aims to be:
 ### Servers
 - **Create** servers with minimal boilerplate using intuitive decorators
 - **Proxy** existing servers to modify configuration or transport
-- **Compose** servers by into complex applications
+- **Compose**  servers into complex applications
 - **Generate** servers from OpenAPI specs or FastAPI objects
 
 ### Clients
diff --git a/src/fastmcp/utilities/func_metadata.py b/src/fastmcp/utilities/func_metadata.py
index 777e7d7..138cb43 100644
--- a/src/fastmcp/utilities/func_metadata.py
+++ b/src/fastmcp/utilities/func_metadata.py
@@ -7,7 +7,15 @@ from typing import (
     ForwardRef,
 )
 
-from pydantic import BaseModel, ConfigDict, Field, WithJsonSchema, create_model
+from pydantic import (
+    BaseModel,
+    ConfigDict,
+    Field,
+    TypeAdapter,
+    ValidationError,
+    WithJsonSchema,
+    create_model,
+)
 from pydantic._internal._typing_extra import eval_type_backport
 from pydantic.fields import FieldInfo
 from pydantic_core import PydanticUndefined
@@ -80,14 +88,18 @@ class FuncMetadata(BaseModel):
         dicts (JSON objects) as JSON strings, which can be pre-parsed here.
         """
         new_data = data.copy()  # Shallow copy
-        for field_name, _field_info in self.arg_model.model_fields.items():
+        for field_name, field_info in self.arg_model.model_fields.items():
             if field_name not in data.keys():
                 continue
             if isinstance(data[field_name], str):
                 try:
                     pre_parsed = json.loads(data[field_name])
-                except json.JSONDecodeError:
-                    continue  # Not JSON - skip
+
+                    # Check if the pre_parsed value is valid for the field
+                    validator = TypeAdapter(field_info.annotation)
+                    validator.validate_python(pre_parsed)
+                except (json.JSONDecodeError, ValidationError):
+                    continue  # Not JSON or invalid for the field
                 if isinstance(pre_parsed, str | int | float):
                     # This is likely that the raw value is e.g. `"hello"` which we
                     # Should really be parsed as '"hello"' in Python - but if we parse


Test patch:
diff --git a/tests/utilities/test_func_metadata.py b/tests/utilities/test_func_metadata.py
index 96d8c6f..9beb27e 100644
--- a/tests/utilities/test_func_metadata.py
+++ b/tests/utilities/test_func_metadata.py
@@ -174,6 +174,74 @@ def test_str_vs_list_str():
     assert result["str_or_list"] == ["hello", "world"]
 
 
+def test_keep_str_as_str():
+    """Test that string arguments are kept as strings"""
+
+    def func_with_str_types(string: str):
+        return string
+
+    meta = func_metadata(func_with_str_types)
+    result = meta.pre_parse_json(
+        {"string": "{'nice to meet you': 'hello', 'goodbye': 5}"}
+    )
+    assert result["string"] == "{'nice to meet you': 'hello', 'goodbye': 5}"
+
+
+def test_missing_annotation():
+    """Test that missing annotations don't cause errors"""
+
+    def fn(x, y):
+        return x + y
+
+    meta = func_metadata(fn)
+    result = meta.pre_parse_json({"x": "1", "y": "2"})
+    assert result["x"] == "1"
+    assert result["y"] == "2"
+
+
+def test_keep_str_union_as_str():
+    """Test that string arguments are kept as strings"""
+
+    def func_with_str_types(string: str | dict[int, str] | None):
+        return string
+
+    meta = func_metadata(func_with_str_types)
+    result = meta.pre_parse_json(
+        {"string": "{'nice to meet you': 'hello', 'goodbye': 5}"}
+    )
+    assert result["string"] == "{'nice to meet you': 'hello', 'goodbye': 5}"
+
+
+def test_keep_str_complex_type_as_str():
+    """Test that string arguments are kept as strings because it's invalid for the field"""
+
+    class SomeModel(BaseModel):
+        x: int
+        y: dict[int, str]
+
+    def func_with_str_types(string: str | SomeModel | None):
+        return string
+
+    meta = func_metadata(func_with_str_types)
+    result = meta.pre_parse_json({"string": '{"x": 1, "y": {"invalid": "hello"}}'})
+    assert result["string"] == '{"x": 1, "y": {"invalid": "hello"}}'
+
+
+def test_convert_str_to_complex_type():
+    """Test that string arguments are converted to the complex type because it's valid for the field"""
+
+    class SomeModel(BaseModel):
+        x: int
+        y: dict[int, str]
+
+    def func_with_str_types(string: str | SomeModel | None):
+        return string
+
+    meta = func_metadata(func_with_str_types)
+    result = meta.pre_parse_json({"string": '{"x": 1, "y": {"1": "hello"}}'})
+    assert result["string"] == {"x": 1, "y": {"1": "hello"}}
+
+
 def test_skip_names():
     """Test that skipped parameters are not included in the model"""