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139 lines
4.2 KiB
Text
139 lines
4.2 KiB
Text
---
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title: tool_transform
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sidebarTitle: tool_transform
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---
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# `fastmcp.tools.tool_transform`
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## Classes
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### `ArgTransform` <sup><a href="https://github.com/jlowin/fastmcp/blob/main/src/fastmcp/tools/tool_transform.py#L85"><Icon icon="github" size="14" /></a></sup>
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Configuration for transforming a parent tool's argument.
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This class allows fine-grained control over how individual arguments are transformed
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when creating a new tool from an existing one. You can rename arguments, change their
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descriptions, add default values, or hide them from clients while passing constants.
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**Examples:**
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Rename argument 'old_name' to 'new_name'
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```python
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ArgTransform(name="new_name")
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```
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Change description only
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```python
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ArgTransform(description="Updated description")
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```
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Add a default value (makes argument optional)
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```python
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ArgTransform(default=42)
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```
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Add a default factory (makes argument optional)
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```python
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ArgTransform(default_factory=lambda: time.time())
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```
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Change the type
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```python
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ArgTransform(type=str)
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```
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Hide the argument entirely from clients
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```python
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ArgTransform(hide=True)
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```
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Hide argument but pass a constant value to parent
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```python
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ArgTransform(hide=True, default="constant_value")
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```
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Hide argument but pass a factory-generated value to parent
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```python
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ArgTransform(hide=True, default_factory=lambda: uuid.uuid4().hex)
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```
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Make an optional parameter required (removes any default)
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```python
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ArgTransform(required=True)
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```
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Combine multiple transformations
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```python
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ArgTransform(name="new_name", description="New desc", default=None, type=int)
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```
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### `TransformedTool` <sup><a href="https://github.com/jlowin/fastmcp/blob/main/src/fastmcp/tools/tool_transform.py#L199"><Icon icon="github" size="14" /></a></sup>
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A tool that is transformed from another tool.
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This class represents a tool that has been created by transforming another tool.
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It supports argument renaming, schema modification, custom function injection,
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and provides context for the forward() and forward_raw() functions.
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The transformation can be purely schema-based (argument renaming, dropping, etc.)
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or can include a custom function that uses forward() to call the parent tool
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with transformed arguments.
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**Methods:**
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#### `from_tool` <sup><a href="https://github.com/jlowin/fastmcp/blob/main/src/fastmcp/tools/tool_transform.py#L280"><Icon icon="github" size="14" /></a></sup>
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```python
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from_tool(cls, tool: Tool, name: str | None = None, description: str | None = None, tags: set[str] | None = None, transform_fn: Callable[..., Any] | None = None, transform_args: dict[str, ArgTransform] | None = None, annotations: ToolAnnotations | None = None, serializer: Callable[[Any], str] | None = None, enabled: bool | None = None) -> TransformedTool
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```
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Create a transformed tool from a parent tool.
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**Args:**
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- `tool`: The parent tool to transform.
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- `transform_fn`: Optional custom function. Can use forward() and forward_raw()
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to call the parent tool. Functions with **kwargs receive transformed
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argument names.
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- `name`: New name for the tool. Defaults to parent tool's name.
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- `transform_args`: Optional transformations for parent tool arguments.
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Only specified arguments are transformed, others pass through unchanged\:
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- Simple rename (str)
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- Complex transformation (rename/description/default/drop) (ArgTransform)
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- Drop the argument (None)
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- `description`: New description. Defaults to parent's description.
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- `tags`: New tags. Defaults to parent's tags.
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- `annotations`: New annotations. Defaults to parent's annotations.
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- `serializer`: New serializer. Defaults to parent's serializer.
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**Returns:**
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- TransformedTool with the specified transformations.
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**Examples:**
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# Transform specific arguments only
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```python
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Tool.from_tool(parent, transform_args={"old": "new"}) # Others unchanged
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```
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# Custom function with partial transforms
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```python
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async def custom(x: int, y: int) -> str:
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result = await forward(x=x, y=y)
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return f"Custom: {result}"
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Tool.from_tool(parent, transform_fn=custom, transform_args={"a": "x", "b": "y"})
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```
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# Using **kwargs (gets all args, transformed and untransformed)
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```python
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async def flexible(**kwargs) -> str:
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result = await forward(**kwargs)
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return f"Got: {kwargs}"
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Tool.from_tool(parent, transform_fn=flexible, transform_args={"a": "x"})
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```
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