OpenManus is an open-source general-purpose AI agent that lets anyone run an autonomous, tool-using assistant without an invite code or a proprietary platform. Released under the permissive MIT license and now past 57,000 GitHub stars, it was built by team members from MetaGPT as a community answer to the closed Manus agent — the prototype was reportedly stood up in about three hours and has been actively developed since. The premise is simple: describe a goal in natural language, and OpenManus plans and executes the steps needed to accomplish it, calling tools like a web browser and a code runtime along the way. ## An Open Alternative to Manus Manus drew a lot of attention as a general AI agent, but access was gated behind invite codes. OpenManus exists to remove that barrier: it is a from-scratch, openly licensed implementation that anyone can clone, configure with their own model keys, and extend. Because it comes from the MetaGPT ecosystem, it inherits a practical, agent-first design philosophy and a fast-moving contributor base, which is a large part of why it accumulated tens of thousands of stars within weeks of launch. ## How It Works OpenManus is a Python project (targeting Python 3.12) that orchestrates a large language model into an agent loop: it reasons about a task, selects an appropriate tool, executes an action, observes the result, and iterates until the goal is met. Configuration lives in a single `config.toml` where you set the model, base URL, and API key, so it works with OpenAI models like GPT-4o out of the box and with any OpenAI-compatible endpoint — including locally hosted models — by changing the base URL. Installation is straightforward via conda or the faster uv package manager. ## Tools and Browser Automation The agent's usefulness comes from its tools. Beyond calling the LLM, OpenManus can run code and, with an optional Playwright install, drive a real web browser to navigate pages, click, and extract information. That browser-automation capability is what turns it from a chatbot into an agent that can carry out multi-step online tasks — researching a topic, gathering data, or filling in a workflow — rather than just answering questions. ## OpenManus-RL and the Roadmap The project is more than a single agent script. Its authors also launched OpenManus-RL, a companion effort dedicated to reinforcement-learning-based tuning methods (such as GRPO) for LLM agents, developed collaboratively with researchers from UIUC. That research track signals an ambition beyond a Manus clone: improving how agents learn to plan and use tools, with the open-source agent serving as a shared experimental platform for the community. ## Trade-offs and Limitations OpenManus depends on external LLM APIs, so running it at any scale means paying per token to a model provider or hosting your own model. The team describes it as a simple implementation, and like all general-purpose agents it can be brittle: multi-step plans sometimes stall, take wrong turns, or need supervision, and giving an agent browser and code-execution access carries real security considerations. Rapid development is a double-edged sword too — features and configuration can shift between versions, so pinning a release is wise for anything beyond experimentation. ## Who Should Use This OpenManus is a strong fit for developers who want to study or build on a general AI agent without a proprietary gatekeeper, researchers experimenting with agent planning and tool use, and tinkerers who want a self-hostable assistant driven by their own model of choice. The MIT license, large and active community, and OpenManus-RL research track make it one of the most accessible starting points for anyone exploring what autonomous LLM agents can do today.