OpenManus

Open-source general autonomous agent from the MetaGPT team — the 'Manus without an invite code': browsing, tool use and multi-step task execution from a simple Python core.

57,458 9,993 Python MITupdated 5 months ago

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Curator's take

The fastest way to feel what a general autonomous agent does: clone, add a model key, hand it a task — the 3-hour-prototype energy that earned 57k stars keeps the codebase small enough to actually read, which makes it a great learning skeleton. But look at the commit graph before betting on it: activity has been quiet for months while the team's focus moved on (OpenManus-RL and beyond), so treat it as a reference implementation, NOT a maintained production framework — for durable agent infrastructure reach for an actively developed harness instead.

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README.md

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👋 OpenManus

Manus is incredible, but OpenManus can achieve any idea without an Invite Code 🛫!

Our team members @Xinbin Liang and @Jinyu Xiang (core authors), along with @Zhaoyang Yu, @Jiayi Zhang, and @Sirui Hong, we are from @MetaGPT. The prototype is launched within 3 hours and we are keeping building!

It's a simple implementation, so we welcome any suggestions, contributions, and feedback!

Enjoy your own agent with OpenManus!

We're also excited to introduce OpenManus-RL, an open-source project dedicated to reinforcement learning (RL)- based (such as GRPO) tuning methods for LLM agents, developed collaboratively by researchers from UIUC and OpenManus.

Project Demo

Installation

We provide two installation methods. Method 2 (using uv) is recommended for faster installation and better dependency management.

Method 1: Using conda

Create a new conda environment:

conda create -n open_manus python=3.12
conda activate open_manus

Clone the repository:

git clone https://github.com/FoundationAgents/OpenManus.git
cd OpenManus

Install dependencies:

pip install -r requirements.txt

Method 2: Using uv (Recommended)

Install uv (A fast Python package installer and resolve

Continue your stack

What teams reach for next — and why each earns a place beside OpenManus. Ranked by curator confidence.

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deepagents

LangChain's batteries-included agent harness on LangGraph — planning, sub-agents with isolated context, filesystem, shell, skills, human-in-the-loop and persistent memory out of the box.

Why it fitsSame job — a batteries-included general autonomous agent that plans, browses and executes multi-step tasks. deepagents is the actively maintained, LangGraph-backed harness; OpenManus is the leaner, quieter reference implementation.

mindshub

MindsDB's pivot: a unified 'Cowork' workspace where you delegate whole projects — apps, research, analysis, scheduled operations — to open-source models you can swap anytime.

Why it fitsBoth answer 'delegate the whole task to an agent' — OpenManus as a minimal open reference you run yourself, MindsHub as a productized workspace with scheduling and a console.