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AI Agents

Autonomous AI agents and multi-agent frameworks.

476 tools · 💎 105 hidden gems

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Start here

The most-starred projects in this category, plus a rotating pick of three more from deeper in the list — refreshed so the whole catalogue gets its turn in the window.

AI Agents

openclaw

A personal AI that really does things — on any OS, with your data staying yours.

★ 391.6k starsMIT
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AI Agents

superpowers

An agentic skills framework & software development methodology that works.

★ 294.9k starsMIT
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AI Agents

ECC

Agent harness optimization system with skills, memory and security for Claude Code, Codex and more

★ 275.2k starsMIT
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AI Agents

labs-molt

A lean, HuggingFace-native RL framework for agentic research.

★ 1.2k starsApache-2.0
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AI Agents

weave

A toolkit for developing AI-powered apps, from the Weights & Biases team.

★ 1.1k starsApache-2.0
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AI Agents

Talorys

Talorys — your personal AI agent in your own Cloudflare account: chat, memory, tasks, notes and scheduled routines, deployed with one command

★ 1.1k starsMIT
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About AI Agents tools

AI agents go beyond chat: they plan multi-step work, call tools, browse, write and run code, and report back. This category spans single-agent frameworks, multi-agent teams where specialised agents collaborate, computer-use agents that operate a desktop, and the harnesses that keep them observable and safe.

The honest dividing line is how much supervision each system needs. Some are research frameworks for building your own agent; others are ready-made workers for coding, research, or browser tasks. Every guide here is explicit about what the agent can actually do today, because this is the category where demos most often outrun reality.

How to choose

  • Start with a narrow, checkable job — codebase questions, research summaries — before giving an agent open-ended work.
  • Prefer frameworks with visible traces and approvals over black boxes; you will debug the agent's reasoning, not just its output.
  • Sandboxing matters: agents that run code should do it in a container or VM, and the good ones say so.
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Questions, answered

Which open-source AI Agents tools are listed here?

This page collects 476 open-source AI Agents projects curated by LibreAI — Autonomous AI agents and multi-agent frameworks. Each one is verified on GitHub and has its own guide page with an overview, install steps, use cases, and an FAQ.

Are these AI Agents tools free to use?

Yes. Every tool here is open source and free to download and use under its own license — most use MIT, Apache-2.0, or GPL-3.0, and any custom source-available license is flagged on the tool's page. Check the LICENSE file before commercial use.

Does LibreAI host these tools?

No. LibreAI publishes guides only — no downloads are served from this site. Every install comes from the project's official GitHub repository.

How do I install a AI Agents tool from this page?

Open the tool's guide and follow its 'Run it yourself' section — the steps come from the project's own documentation — or use the 'View on GitHub' button to go straight to the official repository.

How were these tools chosen?

Every project is verified live through the GitHub API — stars, forks, license, and recent activity — and listed only if it has real momentum and an active community.

Can AI agents really work unsupervised?

Short, well-defined jobs — answering questions about a codebase, drafting research summaries — work well today. Long open-ended tasks still drift, which is why the better frameworks here emphasise traces, checkpoints, and human approvals rather than full autonomy.

Are agents safe to give my computer or accounts to?

Treat an agent like a new contractor: start with limited access, sandboxed environments, and review of consequential actions. The projects in this category differ widely in their safety tooling, and the guides call out the ones with real guardrails.