zeroboot
Sub-millisecond VM sandboxes for AI agents via copy-on-write forking.
NemoClaw es un proyecto de agentes de IA de código abierto de NVIDIA (NVIDIA/NemoClaw en GitHub). Tiene 22.686 estrellas en GitHub y 3.131 bifurcaciones, se publica bajo la licencia Apache-2.0 y se actualizó por última vez en GitHub el 8 de octubre de 2026.
NVIDIA's reference stack for running AI agents more securely inside OpenShell sandboxes
Confirm you have a supported host - the docs target DGX systems or Windows Subsystem for Linux (WSL).
Clone the repository and open the linked quickstart for the agent you want to run.
Run the terminal installer, or let your coding agent install it with you using the official starter prompt.
Accept the express install preset or choose your agent, sandbox name, inference provider and model interactively.
Runs agents inside NVIDIA OpenShell so their work is contained rather than executed directly on the host.
Supports OpenClaw (the express-install default), Hermes and LangChain Deep Agents Code with dedicated quickstarts.
Connects sandboxed agents to managed inference providers and models chosen at install time.
A preset-driven installer configures recommended settings per platform, with an interactive mode when you want control.
An official starter prompt lets Cursor, Claude Code, Codex or Copilot install NemoClaw with you, asking one question at a time.
Ships with docs covering prerequisites, per-agent quickstarts and user guides.
Get the source code from GitHub and enter the project directory.
git clone https://github.com/NVIDIA/NemoClaw.git
cd NemoClawThe README routes installation through the official docs and terminal installer rather than a single package command.
# See the prerequisites and quickstart for your agent in the docs linked from the READMEExpress install sets up OpenClaw by default; other guides cover Hermes and LangChain Deep Agents.
# Pick a quickstart (OpenClaw / Hermes / Deep Agents) from the docs indexIt is maintained by NVIDIA as an open-source reference stack on GitHub.
Yes - NemoClaw is Apache-2.0 licensed and free to use under that license.
The software is free, but inference comes from a provider you choose during setup - that provider may require its own account or API key, and local managed inference depends on your hardware.
Compared with running OpenClaw or a similar agent directly on your machine, NemoClaw adds OpenShell sandboxing and managed inference as the default posture, trading some simplicity for isolation.
Check the prerequisites in the docs, clone the repo, and follow the quickstart for OpenClaw, Hermes or Deep Agents.
Sub-millisecond VM sandboxes for AI agents via copy-on-write forking.
NVIDIA's object-oriented, Pythonic approach to building AI agents.
ByteDance's open-source multimodal AI agent stack: GUI agents that see and operate real desktops
Secure sandboxes where AI agents run real code.
The open runtime for AI agents — a Rust platform for running, governing and routing agents with TokenOps.
NVIDIA's toolkit for connecting, profiling and optimizing teams of AI agents — across any framework
Los demás proyectos de Agentes de IA con más estrellas del catálogo de LibreAI: la lista realista de alternativas si NemoClaw no es lo que buscas.
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Proyectos de Agentes de IA cercanos en el catálogo, los más próximos en estrellas a NemoClaw: sigue explorando a ambos lados.
An MCP server that lets Claude, Cursor and Windsurf build n8n workflows for you
Open-source LLM observability: trace, evaluate and monitor apps and agents
A framework for building agents and services
Yohei Nakajima's autonomous task agent - now a self-building agent framework in Python
One RAG framework for everything — including multimodal documents.
Stanford's Generative Agents simulation - 25 AI characters living in a virtual town
Gratis y abierto: consigue el código fuente, dale una estrella al repositorio y empieza a crear.