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pydantic_ai.builtin_tools

AbstractBuiltinTool dataclass

Bases: ABC

A builtin tool that can be used by an agent.

This class is abstract and cannot be instantiated directly.

The builtin tools are passed to the model as part of the ModelRequestParameters.

Source code in pydantic_ai_slim/pydantic_ai/builtin_tools.py 
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@dataclass(kw_only=True)
class AbstractBuiltinTool(ABC):
    """A builtin tool that can be used by an agent.

    This class is abstract and cannot be instantiated directly.

    The builtin tools are passed to the model as part of the `ModelRequestParameters`.
    """

    kind: str = 'unknown_builtin_tool'
    """Built-in tool identifier, this should be available on all built-in tools as a discriminator."""

    @property
    def unique_id(self) -> str:
        """A unique identifier for the builtin tool.

        If multiple instances of the same builtin tool can be passed to the model, subclasses should override this property to allow them to be distinguished.
        """
        return self.kind

    def __init_subclass__(cls, **kwargs: Any) -> None:
        super().__init_subclass__(**kwargs)
        _BUILTIN_TOOL_TYPES[cls.kind] = cls

    @classmethod
    def __get_pydantic_core_schema__(
        cls, _source_type: Any, handler: pydantic.GetCoreSchemaHandler
    ) -> core_schema.CoreSchema:
        if cls is not AbstractBuiltinTool:
            return handler(cls)

        tools = _BUILTIN_TOOL_TYPES.values()
        if len(tools) == 1:  # pragma: no cover
            tools_type = next(iter(tools))
        else:
            tools_annotated = [Annotated[tool, pydantic.Tag(tool.kind)] for tool in tools]
            tools_type = Annotated[Union[tuple(tools_annotated)], pydantic.Discriminator(_tool_discriminator)]  # noqa: UP007

        return handler(tools_type)

kind class-attribute instance-attribute 

kind: str = 'unknown_builtin_tool'

Built-in tool identifier, this should be available on all built-in tools as a discriminator.

unique_id property 

unique_id: str

A unique identifier for the builtin tool.

If multiple instances of the same builtin tool can be passed to the model, subclasses should override this property to allow them to be distinguished.

WebSearchTool dataclass

Bases: AbstractBuiltinTool

A builtin tool that allows your agent to search the web for information.

The parameters that PydanticAI passes depend on the model, as some parameters may not be supported by certain models.

Supported by:

  • Anthropic
  • OpenAI Responses
  • Groq
  • Google
Source code in pydantic_ai_slim/pydantic_ai/builtin_tools.py 
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@dataclass(kw_only=True)
class WebSearchTool(AbstractBuiltinTool):
    """A builtin tool that allows your agent to search the web for information.

    The parameters that PydanticAI passes depend on the model, as some parameters may not be supported by certain models.

    Supported by:

    * Anthropic
    * OpenAI Responses
    * Groq
    * Google
    """

    search_context_size: Literal['low', 'medium', 'high'] = 'medium'
    """The `search_context_size` parameter controls how much context is retrieved from the web to help the tool formulate a response.

    Supported by:

    * OpenAI Responses
    """

    user_location: WebSearchUserLocation | None = None
    """The `user_location` parameter allows you to localize search results based on a user's location.

    Supported by:

    * Anthropic
    * OpenAI Responses
    """

    blocked_domains: list[str] | None = None
    """If provided, these domains will never appear in results.

    With Anthropic, you can only use one of `blocked_domains` or `allowed_domains`, not both.

    Supported by:

    * Anthropic, see <https://docs.anthropic.com/en/docs/build-with-claude/tool-use/web-search-tool#domain-filtering>
    * Groq, see <https://console.groq.com/docs/agentic-tooling#search-settings>
    """

    allowed_domains: list[str] | None = None
    """If provided, only these domains will be included in results.

    With Anthropic, you can only use one of `blocked_domains` or `allowed_domains`, not both.

    Supported by:

    * Anthropic, see <https://docs.anthropic.com/en/docs/build-with-claude/tool-use/web-search-tool#domain-filtering>
    * Groq, see <https://console.groq.com/docs/agentic-tooling#search-settings>
    """

    max_uses: int | None = None
    """If provided, the tool will stop searching the web after the given number of uses.

    Supported by:

    * Anthropic
    """

    kind: str = 'web_search'
    """The kind of tool."""

search_context_size class-attribute instance-attribute 

search_context_size: Literal["low", "medium", "high"] = (
    "medium"
)

The search_context_size parameter controls how much context is retrieved from the web to help the tool formulate a response.

Supported by:

  • OpenAI Responses

user_location class-attribute instance-attribute 

user_location: WebSearchUserLocation | None = None

The user_location parameter allows you to localize search results based on a user's location.

Supported by:

  • Anthropic
  • OpenAI Responses

blocked_domains class-attribute instance-attribute 

blocked_domains: list[str] | None = None

If provided, these domains will never appear in results.

With Anthropic, you can only use one of blocked_domains or allowed_domains, not both.

Supported by:

allowed_domains class-attribute instance-attribute 

allowed_domains: list[str] | None = None

If provided, only these domains will be included in results.

With Anthropic, you can only use one of blocked_domains or allowed_domains, not both.

Supported by:

max_uses class-attribute instance-attribute 

max_uses: int | None = None

If provided, the tool will stop searching the web after the given number of uses.

Supported by:

  • Anthropic

kind class-attribute instance-attribute 

kind: str = 'web_search'

The kind of tool.

WebSearchUserLocation

Bases: TypedDict

Allows you to localize search results based on a user's location.

Supported by:

  • Anthropic
  • OpenAI Responses
Source code in pydantic_ai_slim/pydantic_ai/builtin_tools.py 
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class WebSearchUserLocation(TypedDict, total=False):
    """Allows you to localize search results based on a user's location.

    Supported by:

    * Anthropic
    * OpenAI Responses
    """

    city: str
    """The city where the user is located."""

    country: str
    """The country where the user is located. For OpenAI, this must be a 2-letter country code (e.g., 'US', 'GB')."""

    region: str
    """The region or state where the user is located."""

    timezone: str
    """The timezone of the user's location."""

city instance-attribute 

city: str

The city where the user is located.

country instance-attribute 

country: str

The country where the user is located. For OpenAI, this must be a 2-letter country code (e.g., 'US', 'GB').

region instance-attribute 

region: str

The region or state where the user is located.

timezone instance-attribute 

timezone: str

The timezone of the user's location.

CodeExecutionTool dataclass

Bases: AbstractBuiltinTool

A builtin tool that allows your agent to execute code.

Supported by:

  • Anthropic
  • OpenAI Responses
  • Google
Source code in pydantic_ai_slim/pydantic_ai/builtin_tools.py 
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@dataclass(kw_only=True)
class CodeExecutionTool(AbstractBuiltinTool):
    """A builtin tool that allows your agent to execute code.

    Supported by:

    * Anthropic
    * OpenAI Responses
    * Google
    """

    kind: str = 'code_execution'
    """The kind of tool."""

kind class-attribute instance-attribute 

kind: str = 'code_execution'

The kind of tool.

UrlContextTool dataclass

Bases: AbstractBuiltinTool

Allows your agent to access contents from URLs.

Supported by:

  • Google
Source code in pydantic_ai_slim/pydantic_ai/builtin_tools.py 
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@dataclass(kw_only=True)
class UrlContextTool(AbstractBuiltinTool):
    """Allows your agent to access contents from URLs.

    Supported by:

    * Google
    """

    kind: str = 'url_context'
    """The kind of tool."""

kind class-attribute instance-attribute 

kind: str = 'url_context'

The kind of tool.

ImageGenerationTool dataclass

Bases: AbstractBuiltinTool

A builtin tool that allows your agent to generate images.

Supported by:

  • OpenAI Responses
  • Google
Source code in pydantic_ai_slim/pydantic_ai/builtin_tools.py 
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@dataclass(kw_only=True)
class ImageGenerationTool(AbstractBuiltinTool):
    """A builtin tool that allows your agent to generate images.

    Supported by:

    * OpenAI Responses
    * Google
    """

    background: Literal['transparent', 'opaque', 'auto'] = 'auto'
    """Background type for the generated image.

    Supported by:

    * OpenAI Responses. 'transparent' is only supported for 'png' and 'webp' output formats.
    """

    input_fidelity: Literal['high', 'low'] | None = None
    """
    Control how much effort the model will exert to match the style and features,
    especially facial features, of input images.

    Supported by:

    * OpenAI Responses. Default: 'low'.
    """

    moderation: Literal['auto', 'low'] = 'auto'
    """Moderation level for the generated image.

    Supported by:

    * OpenAI Responses
    """

    output_compression: int = 100
    """Compression level for the output image.

    Supported by:

    * OpenAI Responses. Only supported for 'png' and 'webp' output formats.
    """

    output_format: Literal['png', 'webp', 'jpeg'] | None = None
    """The output format of the generated image.

    Supported by:

    * OpenAI Responses. Default: 'png'.
    """

    partial_images: int = 0
    """
    Number of partial images to generate in streaming mode.

    Supported by:

    * OpenAI Responses. Supports 0 to 3.
    """

    quality: Literal['low', 'medium', 'high', 'auto'] = 'auto'
    """The quality of the generated image.

    Supported by:

    * OpenAI Responses
    """

    size: Literal['1024x1024', '1024x1536', '1536x1024', 'auto'] = 'auto'
    """The size of the generated image.

    Supported by:

    * OpenAI Responses
    """

    kind: str = 'image_generation'
    """The kind of tool."""

background class-attribute instance-attribute 

background: Literal["transparent", "opaque", "auto"] = (
    "auto"
)

Background type for the generated image.

Supported by:

  • OpenAI Responses. 'transparent' is only supported for 'png' and 'webp' output formats.

input_fidelity class-attribute instance-attribute 

input_fidelity: Literal['high', 'low'] | None = None

Control how much effort the model will exert to match the style and features, especially facial features, of input images.

Supported by:

  • OpenAI Responses. Default: 'low'.

moderation class-attribute instance-attribute 

moderation: Literal['auto', 'low'] = 'auto'

Moderation level for the generated image.

Supported by:

  • OpenAI Responses

output_compression class-attribute instance-attribute 

output_compression: int = 100

Compression level for the output image.

Supported by:

  • OpenAI Responses. Only supported for 'png' and 'webp' output formats.

output_format class-attribute instance-attribute 

output_format: Literal['png', 'webp', 'jpeg'] | None = None

The output format of the generated image.

Supported by:

  • OpenAI Responses. Default: 'png'.

partial_images class-attribute instance-attribute 

partial_images: int = 0

Number of partial images to generate in streaming mode.

Supported by:

  • OpenAI Responses. Supports 0 to 3.

quality class-attribute instance-attribute 

quality: Literal['low', 'medium', 'high', 'auto'] = 'auto'

The quality of the generated image.

Supported by:

  • OpenAI Responses

size class-attribute instance-attribute 

size: Literal[
    "1024x1024", "1024x1536", "1536x1024", "auto"
] = "auto"

The size of the generated image.

Supported by:

  • OpenAI Responses

kind class-attribute instance-attribute 

kind: str = 'image_generation'

The kind of tool.

MemoryTool dataclass

Bases: AbstractBuiltinTool

A builtin tool that allows your agent to use memory.

Supported by:

  • Anthropic
Source code in pydantic_ai_slim/pydantic_ai/builtin_tools.py 
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@dataclass(kw_only=True)
class MemoryTool(AbstractBuiltinTool):
    """A builtin tool that allows your agent to use memory.

    Supported by:

    * Anthropic
    """

    kind: str = 'memory'
    """The kind of tool."""

kind class-attribute instance-attribute 

kind: str = 'memory'

The kind of tool.

MCPServerTool dataclass

Bases: AbstractBuiltinTool

A builtin tool that allows your agent to use MCP servers.

Supported by:

  • OpenAI Responses
  • Anthropic
Source code in pydantic_ai_slim/pydantic_ai/builtin_tools.py 
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@dataclass(kw_only=True)
class MCPServerTool(AbstractBuiltinTool):
    """A builtin tool that allows your agent to use MCP servers.

    Supported by:

    * OpenAI Responses
    * Anthropic
    """

    id: str
    """A unique identifier for the MCP server."""

    url: str
    """The URL of the MCP server to use.

    For OpenAI Responses, it is possible to use `connector_id` by providing it as `x-openai-connector:<connector_id>`.
    """

    authorization_token: str | None = None
    """Authorization header to use when making requests to the MCP server.

    Supported by:

    * OpenAI Responses
    * Anthropic
    """

    description: str | None = None
    """A description of the MCP server.

    Supported by:

    * OpenAI Responses
    """

    allowed_tools: list[str] | None = None
    """A list of tools that the MCP server can use.

    Supported by:

    * OpenAI Responses
    * Anthropic
    """

    headers: dict[str, str] | None = None
    """Optional HTTP headers to send to the MCP server.

    Use for authentication or other purposes.

    Supported by:

    * OpenAI Responses
    """

    kind: str = 'mcp_server'

    @property
    def unique_id(self) -> str:
        return ':'.join([self.kind, self.id])

id instance-attribute 

id: str

A unique identifier for the MCP server.

url instance-attribute 

url: str

The URL of the MCP server to use.

For OpenAI Responses, it is possible to use connector_id by providing it as x-openai-connector:<connector_id>.

authorization_token class-attribute instance-attribute 

authorization_token: str | None = None

Authorization header to use when making requests to the MCP server.

Supported by:

  • OpenAI Responses
  • Anthropic

description class-attribute instance-attribute 

description: str | None = None

A description of the MCP server.

Supported by:

  • OpenAI Responses

allowed_tools class-attribute instance-attribute 

allowed_tools: list[str] | None = None

A list of tools that the MCP server can use.

Supported by:

  • OpenAI Responses
  • Anthropic

headers class-attribute instance-attribute 

headers: dict[str, str] | None = None

Optional HTTP headers to send to the MCP server.

Use for authentication or other purposes.

Supported by:

  • OpenAI Responses