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

Our team members @Xinbing 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.

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

1. Create a new conda environment:

conda create -n open_manus python=3.12
conda activate open_manus

2. Clone the repository:

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

3. Install dependencies:

pip install -r requirements.txt

1. Install uv (A fast Python package installer and resolver):

curl -LsSf https://astral.sh/uv/install.sh | sh

2. Clone the repository:

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

3. Create a new virtual environment and activate it:

uv venv --python 3.12
source .venv/bin/activate  # On Unix/macOS
# Or on Windows:
# .venv\Scripts\activate

4. Install dependencies:

uv pip install -r requirements.txt

OpenManus starts Browser Use CLI 3.0 as a default MCP server:

uvx browser-use --cli-mcp

uvx keeps Browser Use and its fast-moving dependencies isolated from the OpenManus environment. The agent receives the canonical Browser Use skill and the native browser_exec and browser_screenshot tools.

Local mode attaches to Chrome or Chromium automatically and needs no API key. For diagnostics or to install Chromium, run:

uvx browser-use --doctor
uvx browser-use install

For an isolated Browser Use Cloud browser, authenticate before starting OpenManus. The agent can then start and select a named remote browser:

export BROWSER_USE_API_KEY="bu_..."

Existing browsers can be selected with BU_CDP_URL, BU_CDP_WS, or BU_NAME. Set OPENMANUS_DISABLE_BROWSER_USE=1 to disable the default Browser Use MCP server.

BrowserGym still requires its Playwright browser:

playwright install

OpenManus requires configuration for the LLM APIs it uses. Follow these steps to set up your configuration:

1. Create a config.toml file in the config directory (you can copy from the example):

cp config/config.example.toml config/config.toml

2. Edit config/config.toml to add your API keys and customize settings:

# Global LLM configuration
[llm]
model = "gpt-4o"
base_url = "https://api.openai.com/v1"
api_key = "sk-..."  # Replace with your actual API key
max_tokens = 4096
temperature = 0.0

# Optional configuration for specific LLM models
[llm.vision]
model = "gpt-4o"
base_url = "https://api.openai.com/v1"
api_key = "sk-..."  # Replace with your actual API key

One line for run OpenManus:

python main.py

Then input your idea via terminal!

For MCP tool version, you can run:

python run_mcp.py

For unstable multi-agent version, you also can run:

python run_flow.py

Currently, besides the general OpenManus Agent, we have also integrated the DataAnalysis Agent, which is suitable for data analysis and data visualization tasks. You can add this agent to run_flow in config.toml.

# Optional configuration for run-flow
[runflow]
use_data_analysis_agent = true     # Disabled by default, change to true to activate

In addition, you need to install the relevant dependencies to ensure the agent runs properly: Detailed Installation Guide

We welcome any friendly suggestions and helpful contributions! Just create issues or submit pull requests.

Or contact @mannaandpoem via 📧email: mannaandpoem@gmail.com

Note: Before submitting a pull request, please use the pre-commit tool to check your changes. Run pre-commit run --all-files to execute the checks.

Join our networking group on Feishu and share your experience with other developers!

Thanks to PPIO for computing source support.

PPIO: The most affordable and easily-integrated MaaS and GPU cloud solution.

Thanks to anthropic-computer-use, browser-use and crawl4ai for providing basic support for this project!

Additionally, we are grateful to AAAJ, MetaGPT, OpenHands and SWE-agent.

We also thank stepfun(阶跃星辰) for supporting our Hugging Face demo space.

OpenManus is built by contributors from MetaGPT. Huge thanks to this agent community!

@misc{openmanus2025,
  author = {Xinbing Liang and Jinyu Xiang and Zhaoyang Yu and Jiayi Zhang and Sirui Hong and Sheng Fan and Xiao Tang and Bang Liu and Yuyu Luo and Chenglin Wu},
  title = {OpenManus: An open-source framework for building general AI agents},
  year = {2025},
  publisher = {Zenodo},
  doi = {10.5281/zenodo.15186407},
  url = {https://doi.org/10.5281/zenodo.15186407},
}