# fastmcp.prompts.base

Base classes for FastMCP prompts.

## Classes

### Message

Wrapper for prompt message with auto-serialization. Accepts any content - strings pass through, other types (dict, list, BaseModel) are JSON-serialized to text. **Methods:**

#### to_mcp_prompt_message

```python
to_mcp_prompt_message(self) -> PromptMessage
```
Convert to MCP PromptMessage.

### PromptArgument

An argument that can be passed to a prompt.

### PromptResult

Canonical result type for prompt rendering. Provides explicit control over prompt responses: multiple messages, roles, and metadata at both the message and result level. **Methods:**

#### to_mcp_prompt_result

```python
to_mcp_prompt_result(self) -> GetPromptResult
```
Convert to MCP GetPromptResult.

### Prompt

A prompt template that can be rendered with parameters. **Methods:**

#### to_mcp_prompt

```python
to_mcp_prompt(self, **overrides: Any) -> SDKPrompt
```
Convert the prompt to an MCP prompt.

#### from_function

```python
from_function(cls, fn: Callable[..., Any]) -> FunctionPrompt
```
Create a Prompt from a function. The function can return:

- str: wrapped as single user Message
- list[Message | str]: converted to list[Message]
- PromptResult: used directly

#### render

```python
render(self, arguments: dict[str, Any] | None = None) -> str | list[Message | str] | PromptResult
```
Render the prompt with arguments. Subclasses must implement this method. Return one of:

- str: Wrapped as single user Message
- list[Message | str]: Converted to list[Message]
- PromptResult: Used directly

#### convert_result

```python
convert_result(self, raw_value: Any) -> PromptResult
```
Convert a raw return value to PromptResult. **Raises:**

- `TypeError`: for unsupported types

#### register_with_docket

```python
register_with_docket(self, docket: Docket) -> None
```
Register this prompt with docket for background execution.

#### add_to_docket

```python
add_to_docket(self, docket: Docket, arguments: dict[str, Any] | None, **kwargs: Any) -> Execution
```
Schedule this prompt for background execution via docket. **Args:**

- `docket`: The Docket instance
- `arguments`: Prompt 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()

#### get_span_attributes

```python
get_span_attributes(self) -> dict[str, Any]
```