Anthropic Claude

Install the Anthropic model extra, set an API key, and pass Claude to an Agent.

Installation

uv pip install -U "agno[anthropic]"

Authentication

Set the ANTHROPIC_API_KEY environment variable. Create a key in the Claude Console.

export ANTHROPIC_API_KEY="your_anthropic_api_key"

Example

from agno.agent import Agent
from agno.models.anthropic import Claude

agent = Agent(
    model=Claude(id="claude-sonnet-4-5-20250929"),
    markdown=True,
)

if __name__ == "__main__":
    agent.print_response("Write a two-sentence horror story.")

Save the example as agent.py, then run:

python agent.py

See the basic usage guide for the complete environment setup.

Model Selection

Claude defaults to claude-sonnet-4-5-20250929. Pass another model ID with Claude(id=...) when a different capability or latency profile fits the use case.

Model	Use Case
`claude-sonnet-4-5-20250929`	Balanced speed and intelligence
`claude-opus-4-5`	Complex agentic coding and enterprise work
`claude-haiku-4-5-20251001`	Fast, cost-sensitive workloads
`claude-sonnet-4-6`	Long-running agent workflows

See Anthropic's current model comparison and model lifecycle table before deploying a pinned model.

Claude 4.5 model IDs use dated snapshots. Shorter names such as claude-sonnet-4-5 are aliases. Starting with Claude 4.6, dateless IDs such as claude-sonnet-4-6 are canonical pinned versions, not rolling aliases.

Supported Input

Input	Agno Support
Text	Text input and text output
Images	JPEG, PNG, GIF, and WebP from a URL, local path, or bytes. Anthropic analyzes only the first frame of an animated GIF.
PDFs	PDF documents from a URL, local path, bytes, or Anthropic file ID
Text documents	UTF-8 content, including `.txt`, `.csv`, and `.md`, from a URL, local path, bytes, or Anthropic file ID
Audio and video	Unsupported. The adapter omits these inputs and logs a warning.

Agno sends image URLs to Anthropic as base64 data after downloading them. Anthropic's request-size, image-size, page-count, and model limits still apply. See the vision limits and PDF limits.

Request Limits

The Messages API requires max_tokens. Agno sends 8192 unless max_tokens is set on Claude. Anthropic also accepts 0 for prompt-cache pre-warming, but Agno omits that falsy value; use a positive value with this adapter. See the Messages API reference.

Anthropic also applies organization and workspace rate limits. See the rate-limit documentation.

Beta Features

Pass exact Anthropic beta names with betas. Features that add request fields also need their matching Agno parameters. This context-editing configuration sends both the required beta and request body:

from agno.agent import Agent
from agno.models.anthropic import Claude

agent = Agent(
    model=Claude(
        id="claude-sonnet-4-5-20250929",
        betas=["context-management-2025-06-27"],
        context_management={
            "edits": [{"type": "clear_tool_uses_20250919"}],
        },
    ),
)

See beta features with Claude and context editing.

Prompt Caching

Set cache_system_prompt=True to add a prompt-cache breakpoint to the agent's system prompt:

from agno.agent import Agent
from agno.models.anthropic import Claude

agent = Agent(
    model=Claude(
        id="claude-sonnet-4-5-20250929",
        cache_system_prompt=True,
    ),
)

See prompt caching with Claude.

Structured Outputs

Pass a Pydantic model as output_schema to use Claude's native structured outputs. Select a supported model from the Claude 4.5 families or later, checking Anthropic's current compatibility and lifecycle tables below.

Agno merges the generated JSON schema into output_config.format, preserving other output settings such as effort. It also adds the structured-outputs-2025-11-13 beta header automatically.

from agno.agent import Agent
from agno.models.anthropic import Claude
from pydantic import BaseModel


class User(BaseModel):
    name: str
    age: int
    email: str


agent = Agent(
    model=Claude(id="claude-sonnet-4-5-20250929"),
    description="Extract user information.",
    output_schema=User,
)

See Anthropic's structured-output compatibility and the Agno guides:

Params

Parameter	Type	Default	Description
`id`	`str`	`"claude-sonnet-4-5-20250929"`	Anthropic Claude model ID
`name`	`str`	`"Claude"`	Model name
`provider`	`str`	`"Anthropic"`	Model provider
`max_tokens`	`Optional[int]`	`8192`	Maximum output tokens. Agno sends only truthy values, so Anthropic's `0`-token cache pre-warming is unavailable through this adapter.
`thinking`	`Optional[Dict[str, Any]]`	`None`	Model-specific thinking configuration
`output_config`	`Optional[Dict[str, Any]]`	`None`	Anthropic output configuration, such as `{"effort": "medium"}`. Structured outputs merge the generated schema into `format` while preserving other settings.
`temperature`	`Optional[float]`	`None`	Sampling temperature when supported by the selected model
`stop_sequences`	`Optional[List[str]]`	`None`	Strings that stop generation
`top_p`	`Optional[float]`	`None`	Nucleus-sampling value when supported by the selected model
`top_k`	`Optional[int]`	`None`	Top-k sampling value when supported by the selected model
`cache_system_prompt`	`Optional[bool]`	`False`	Add cache control to the agent-built system prompt
`extended_cache_time`	`Optional[bool]`	`False`	Use a one-hour cache TTL instead of the default five minutes
`cache_tools`	`bool`	`False`	Add cache control to the last tool definition
`system_prompt_blocks`	`Optional[Union[List[SystemPromptBlock], Callable[[], List[SystemPromptBlock]]]]`	`None`	System-prompt blocks with per-block cache controls. A callable is evaluated for each request.
`request_params`	`Optional[Dict[str, Any]]`	`None`	Additional Anthropic request parameters. These are applied after the dedicated fields above.
`betas`	`Optional[List[str]]`	`None`	Exact Anthropic beta names sent through the SDK's beta Messages API
`context_management`	`Optional[Dict[str, Any]]`	`None`	Anthropic context-management request body. Add the beta required by the selected strategy to `betas`.
`mcp_servers`	`Optional[List[MCPServerConfiguration]]`	`None`	Remote MCP server configurations. The legacy connector uses `mcp-client-2025-04-04`; the current `mcp-client-2025-11-20` contract also requires MCP toolsets in `tools`. Follow the connector migration instead of changing only the header.
`skills`	`Optional[List[Dict[str, str]]]`	`None`	Agent Skills to load, such as `[{"type": "anthropic", "skill_id": "pptx", "version": "latest"}]`. Agno adds the Skills beta, the legacy code-execution beta, and the `code_execution_20250825` tool.
`citations`	`bool`	`True`	Attach citations to URL, local, and bytes document blocks. Agno omits citations from Anthropic file-ID blocks and suppresses them when structured output is active.
`append_trailing_user_message`	`Optional[bool]`	`None`	Append a user turn when a conversation ends with an assistant message. When unset, Agno enables this if the model does not support assistant prefill or effective thinking is enabled. `request_params["thinking"]` overrides the dedicated `thinking` field; an explicit value for this option is respected.
`trailing_user_message_content`	`str`	`"continue"`	Content of the appended user message
`api_key`	`Optional[str]`	`None`	Anthropic API key. Falls back to `ANTHROPIC_API_KEY`.
`auth_token`	`Optional[str]`	`None`	Anthropic auth token. Falls back to `ANTHROPIC_AUTH_TOKEN`.
`default_headers`	`Optional[Dict[str, Any]]`	`None`	Default headers for every request
`timeout`	`Optional[float]`	`None`	Request timeout in seconds
`http_client`	`Optional[Union[httpx.Client, httpx.AsyncClient]]`	`None`	Custom synchronous or asynchronous HTTPX client
`client_params`	`Optional[Dict[str, Any]]`	`None`	Additional Anthropic client constructor parameters
`client`	`Optional[AnthropicClient]`	`None`	Preconfigured synchronous Anthropic client
`async_client`	`Optional[AsyncAnthropicClient]`	`None`	Preconfigured asynchronous Anthropic client

Claude is a subclass of the Model class and supports the inherited model parameters.

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