AgentToolDrop

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Strands Agents

Runs a model-driven agent loop in your own process, in Python or TypeScript, with any model provider

Install with pip

pip install strands-agents strands-agents-tools

Copied from the project's docs at github.com/strands-agents/harness-sdk

Why you'd want it

Strands is an SDK for cases where you would otherwise write your own agent loop: it runs in your process with no hosted control plane and covers turn limits, token budgets, cancellation, tools, structured output, MCP, multi-agent patterns, memory, sessions, streaming, guardrails, tracing and evals. It has first-class support for Amazon Bedrock, Anthropic, OpenAI and Gemini plus other and custom providers, and hooks let you intercept any step of the loop. Strands harness (create_harness() in Python, createHarness() in TypeScript) gives a fully assembled agent with preset defaults.

Best for

  • Replacing a hand-rolled agent loop
  • Amazon Bedrock users
  • Mixed Python and TypeScript stacks

Use it when

You want to own the agent loop in your own process, with lifecycle limits, hooks and tracing built in and the option to swap model providers.

Skip it if

You want a hosted agent platform rather than a library. The Python SDK needs Python 3.10+ and the TypeScript SDK needs Node.js 22+.

Editor's note

The repo was renamed from strands-agents/sdk-python to strands-agents/harness-sdk and is now a monorepo with the Python and TypeScript SDKs, Strands harness and the docs site.

Related tools

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    OpenAI Agents SDK

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    Builds multi-agent workflows with handoffs, guardrails, sessions and built-in tracing

    • score 61
    • 30k stars
    • pushed
    • v0.23.1 on
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    Install with pip

    pip install openai-agents
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    Why you'd want it

    The OpenAI Agents SDK is a lightweight Python framework where agents are LLMs configured with instructions, tools, guardrails and handoffs to other agents. It is provider-agnostic, supporting the OpenAI Responses and Chat Completions APIs plus 100+ other LLMs, and includes sessions for conversation history, human-in-the-loop, and built-in tracing of agent runs. It also covers sandbox agents that work in a container over long tasks, plus realtime and voice agents.

    Best for

    • Multi-agent apps with handoffs
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    • Teams on the OpenAI API

    Use it when

    You want a small set of primitives (agents, tools, handoffs, guardrails) with tracing built in, and may want voice or sandboxed agents later.

    Skip it if

    You work in JavaScript or TypeScript; use the separate Agents SDK JS/TS (openai/openai-agents-js) instead. The Python package needs Python 3.10 or newer.

    Stats

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    Claude Agent SDK

    Framework

    Embeds Claude Code's agent loop, built-in tools and context management in Python or TypeScript apps

    • score 61
    • 8.3k stars
    • pushed
    • v0.2.167 on
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    Install with pip

    pip install claude-agent-sdk
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    Why you'd want it

    The Agent SDK is a library that runs the Claude Code binary, so your agent gets the same tools (read, write and edit files, run commands, search the web), agent loop and context management that power Claude Code. You can add custom tools as in-process MCP servers, run hooks at points in the agent lifecycle, spawn subagents, control which tools run automatically through permissions, and resume or fork sessions. It is available for Python (claude-agent-sdk) and TypeScript (@anthropic-ai/claude-agent-sdk).

    Best for

    • Agents that edit files and run commands
    • Teams already using Claude Code
    • Embedding a coding agent in your own app

    Use it when

    You want Claude Code's tool set and permission model inside a process you operate, instead of writing the tool loop yourself.

    Skip it if

    You want to use non-Claude models. It needs an Anthropic API key or Claude through Amazon Bedrock, Google Cloud or Microsoft Foundry, and third-party products may not offer claude.ai login unless approved by Anthropic.

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  3. Rank 65

    smolagents

    Framework

    Runs agents that write their actions as Python code, with core agent logic in about 1,000 lines

    • score 34
    • 29.8k stars
    • pushed
    • v1.26.0 on
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    Install with pip

    pip install "smolagents[toolkit]"
    Use it when, skip it if, stats for smolagents

    Why you'd want it

    smolagents keeps abstractions minimal: the agent logic fits in roughly 1,000 lines, and its CodeAgent writes its actions in code. It is model-agnostic (local transformers or Ollama models, Hugging Face inference providers, or OpenAI, Anthropic and others via LiteLLM) and can use tools from MCP servers, LangChain or Hub Spaces. Agents and tools can be pushed to and pulled from the Hugging Face Hub, and a smolagent CLI runs agents from the terminal.

    Best for

    • Agents that act by writing code
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    Use it when

    You want a small, readable agent library and agents that act by writing code, with your choice of local or hosted models.

    Skip it if

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For agents

The same entry, as files an agent can read without scraping this page. 

# read one entry
curl -s https://agenttooldrop.com/tools/strands-agents.md

# list the MCP servers in the catalog
curl -s https://agenttooldrop.com/tools.json \
  | jq -r '.tools[] | select(.category=="mcp-server") | .slug'