375,000 GitHub stars, a GitHub stars trajectory never seen before. And some backdraws, such as a supply chain attack (ClawHavoc, early 2026) that planted malicious code in 341 third-party extensions. We are talking about the AI agent OpenClaw. And some alternatives …

OpenClaw

OpenClaw · GitHub

OpenClaw connects LLMs to your local machine via a Gateway daemon (systemd/LaunchAgent). Messaging platforms — WhatsApp, Telegram, Slack, Signal — are its UI. Tasks execute through 100+ preconfigured AgentSkills covering shell, browser, APIs, and file system. Memory and config live as plain Markdown/YAML under ~/.openclaw - pretty comfortable. It is Model-agnostic; you can swap between Anthropic, OpenAI, Google, local inference models, or any other model with an OpenAI-compatible endpoint.

User message → Channel (Telegram/Slack/…) → Gateway daemon
             → LLM → Skill execution (shell, browser, API, fs)
             → Result back to channel

The agent runs with the permissions of your user account. No sandbox. No approval gate by default. Palo Alto Networks engineers called it a “security nightmare.” That is the cost of the convenience.

Hermes Agent — maximum control with a bigger footprint

GitHub: hermes

Hermes is a solid alternative in Python. If your stack is not Python-native, you are carrying a fat runtime dependency before you write a single line of agent logic. No pre-built skill marketplace: every integration is hand-rolled using LangChain, litellm, or custom tools. What you get in return is control over every tool the agent can call. Pick it for ML pipelines, data workflows, and custom tool orchestration — not for general productivity automation.

Nemoclaw — containerized, GPU-native, air-gapped

GitHub: nemoclaw

NVIDIA NemoClaw is an open‑source reference stack designed to make running OpenClaw always‑on assistants safer and easier. It installs the NVIDIA OpenShell runtime, a component of the NVIDIA Agent Toolkit, which adds enhanced security controls for autonomous agent execution. No external API keys by default, no cloud dependency, high local inference throughput on NVIDIA hardware, with the trade-off of needing NVIDIA GPUs and hugging the NVIDIA ecosystem.

AutoGPT — Several years as an open source project

GitHub: AutoGPT

AutoGPT is essentially a platform for building and running continuous AI agents—systems that can operate autonomously, carry out multi‑step tasks, and automate complex workflows without constant human intervention.

Written in Python and TS.

n8n — “no code” automation platform

GitHub: n8n

n8n is a workflow automation platform that gives technical teams the flexibility of code with the speed of no-code. With 400+ integrations, native AI capabilities, and a fair-code license, n8n lets you build automations defined with routing and control blocks in a graphical way.

Summary

OpenClaw delivers a fast path from idea to running agents. Hermes gives full control and the beautiful cleanliness of Python. Nemoclaw is the containerized, air-gapped answer with OpenClaw on NVIDIA hardware. AutoGPT fits batch, goal-decomposition workflows without the overhead of a persistent daemon. n8n belongs in the ops toolkit when your workflow shall be deterministic.

References

• OpenClaw: https://openclaw.ai
• https://github.com/openclaw/openclaw
• OpenClaw security analysis: https://www.helpnetsecurity.com/2026/02/12/openclaw-scanner-open-source-tool-detects-autonomous-ai-agents/
• comparison deep-dive
• AutoGPT: https://agpt.co
• https://github.com/Significant-Gravitas/AutoGPT
• n8n: https://n8n.io
• https://github.com/n8n-io/n8n