Comparisons / Anthropic Agent SDK vs Smolagents

Anthropic Agent SDK vs Smolagents: Which Agent Framework to Use?

The Anthropic Agent SDK packages Claude Code's agent loop as a library. Smolagents is HuggingFace's minimalist agent library. Here is how they compare — paradigm, ecosystem, and the use cases each one is actually built for.

By the numbers

Anthropic Agent SDK

GitHub Stars

3.1k

Forks

582

Language

Python

License

MIT

Created

2023-01-17

Created by

Anthropic

Backed by

Google, Spark Capital

Production ready

Yes

github.com/anthropics/anthropic-sdk-python

Smolagents

GitHub Stars

26.4k

Forks

2.4k

Language

Python

License

Apache-2.0

Created

2024-12-05

Created by

Hugging Face

github.com/huggingface/smolagents

GitHub stats as of April 2026. Stars indicate community interest, not necessarily quality or fit for your use case.

ConceptAnthropic Agent SDKSmolagents
AgentClaude agent with built-in tools, MCP servers, and system prompt`CodeAgent` or `ToolCallingAgent` with model and tools list
ToolsBuilt-in tools (`bash`, file read/write, web) + MCP server connections`@tool` decorator or `Tool` class with name, description, and callable
Agent LoopSDK's internal agentic loop with automatic tool dispatchInternal loop: think (LLM reasons), act (code/tool call), observe (result)
Sub-AgentsAgents invoke other agents as tools via the SDK
Lifecycle Hooks18 hook events: pre/post tool call, message, error, etc.
MCP IntegrationOne-line MCP server config for Playwright, Slack, GitHub, etc.
Code Actions`CodeAgent` writes Python code as its action, executed in sandbox
SandboxE2B, Docker, Modal, or Pyodide sandbox for safe code execution
Model SupportHuggingFace Hub models, OpenAI, Anthropic, local via LiteLLM

Anthropic Agent SDK vs Smolagents, head to head

Anthropic Agent SDK The Anthropic Agent SDK packages Claude Code's agent loop as a library.

Smolagents Smolagents is HuggingFace's minimalist agent library.

Both wrap the same underlying agent pattern — an LLM call, a tool dispatch, a loop — in different abstractions. The choice between them is mostly about which mental model and ecosystem fits the team you have, not which one is technically more capable.

Pick Anthropic Agent SDK if

Pick Anthropic Agent SDK if the Anthropic Agent SDK's real value is packaging Claude Code's battle-tested agent loop with built-in tools and MCP integration. If you want a production agent that reads files, runs commands, and connects to services, it saves significant plumbing. For understanding how agents work, the plain version is more instructive. Anthropic Agent SDK is the right fit when the tradeoffs in its intro line up with how your team actually wants to work day-to-day; Smolagents would force you to translate.

Full Anthropic Agent SDKcomparison →

Pick Smolagents if

Pick Smolagents if smolagents lives up to its name — it's genuinely minimal and the code-agent approach is a real innovation that reduces LLM calls by ~30%. If you want a lightweight agent library with HuggingFace ecosystem access, it's excellent. For understanding the fundamentals, the plain version is even simpler. Smolagents is the right fit when the tradeoffs in its intro line up with how your team actually wants to work day-to-day; Anthropic Agent SDK would force you to translate.

Full Smolagentscomparison →

What both add

Both Anthropic Agent SDK and Smolagents pull in a class hierarchy and a dependency tree to wrap what is, at the core, an HTTP POST in a while loop. If your use case is straightforward — one provider, a handful of tools, a single agent — the framework cost may exceed the framework benefit. The lesson below shows the same pattern in ~60 lines without either dependency.

Or build your own in 60 lines

Both Anthropic Agent SDK and Smolagents implement the same 8 patterns. An agent is a function. Tools are a dict. The loop is a while loop. The whole thing composes in ~60 lines of Python.

No framework. No dependencies. No opinions. Just the code.

Build it from scratch →