---
title: function_tool
sidebarTitle: function_tool
---
# `fastmcp.tools.function_tool`
Standalone @tool decorator for FastMCP.
## Functions
### `tool`
```python
tool(name_or_fn: str | Callable[..., Any] | None = None) -> Any
```
Standalone decorator to mark a function as an MCP tool.
Returns the original function with metadata attached. Register with a server
using mcp.add_tool().
## Classes
### `DecoratedTool`
Protocol for functions decorated with @tool.
### `ToolMeta`
Metadata attached to functions by the @tool decorator.
### `FunctionTool`
**Methods:**
#### `to_mcp_tool`
```python
to_mcp_tool(self, **overrides: Any) -> mcp.types.Tool
```
Convert the FastMCP tool to an MCP tool.
Extends the base implementation to add task execution mode if enabled.
#### `from_function`
```python
from_function(cls, fn: Callable[..., Any]) -> FunctionTool
```
Create a FunctionTool from a function.
**Args:**
- `fn`: The function to wrap
- `metadata`: ToolMeta object with all configuration. If provided,
individual parameters must not be passed.
- `name, title, etc.`: Individual parameters for backwards compatibility.
Cannot be used together with metadata parameter.
#### `run`
```python
run(self, arguments: dict[str, Any]) -> ToolResult
```
Run the tool with arguments.
#### `register_with_docket`
```python
register_with_docket(self, docket: Docket) -> None
```
Register this tool with docket for background execution.
FunctionTool registers the underlying function, which has the user's
Depends parameters for docket to resolve.
#### `add_to_docket`
```python
add_to_docket(self, docket: Docket, arguments: dict[str, Any], **kwargs: Any) -> Execution
```
Schedule this tool for background execution via docket.
FunctionTool splats the arguments dict since .fn expects **kwargs.
**Args:**
- `docket`: The Docket instance
- `arguments`: Tool arguments
- `fn_key`: Function lookup key in Docket registry (defaults to self.key)
- `task_key`: Redis storage key for the result
- `**kwargs`: Additional kwargs passed to docket.add()