OpenClaw vs Hermes Agent: Two Open-Source Personal AI Agents Compared

OpenClaw and Hermes Agent are both open-source, MIT-licensed personal AI agents that you install yourself, connect to a model of your choice and talk to through chat apps such as Telegram, WhatsApp, Slack and Discord. The short version: OpenClaw is built around a local "Gateway" that keeps your state, memory and credentials on your own hardware and reaches a very wide range of chat channels and native apps; Hermes Agent, from Nous Research, is built around a learning loop that turns completed tasks into reusable skills, and is designed to run as easily on a cloud VM or serverless sandbox as on your laptop. Either can be self-hosted for the cost of a server and your model usage, or run on managed hosting.

The details below come from each project's own README and documentation, checked on 23 October 2026. Both projects move quickly; re-check versions and install commands before you start.

At a glance

OpenClaw

The OpenClaw README describes it as "an open-source AI assistant that runs on your own computer and meets you in the channels you already use". One Gateway runs it either as a personal assistant on a laptop or as a shared team deployment; the project says "configuration is the only difference".

Its pitch is ownership: "State, memory, and credentials live on your hardware." Models and agent harnesses are plugins you can swap. By default, OpenClaw itself contacts its servers only for a daily version check, anonymous feature statistics are opt-in, and both can be switched off. The project is stewarded by the OpenClaw Foundation, and the README states that "OpenAI is a donor, not an owner".

Installation is a one-line script for macOS, Linux and WSL2 or a PowerShell command on Windows, or an npm package for people who already manage Node.js (the README lists Node 24.16+ or 26.1+). Onboarding verifies model access, creates the workspace and configures the Gateway; the Control UI then lets you send a first message. Tools, skills and plugins extend what it can do, and community skills are shared through ClawHub.

Hermes Agent

The Hermes Agent README calls it "the self-improving AI agent built by Nous Research". Its distinguishing feature is the learning loop: it "creates skills from experience, improves them during use", searches its own past conversations and builds a model of the user across sessions. It is compatible with the agentskills.io standard.

Hermes leans towards running away from your laptop. The README lists six built-in terminal backends — local, Docker, SSH, Modal, Daytona and Vercel Sandbox — and says Daytona and Modal let the environment hibernate when idle. It also has a built-in cron scheduler for unattended reports and backups, and can spawn isolated subagents for parallel work. You switch model providers with a single command. Installation is a script for Linux, macOS and WSL2, a native PowerShell installer for Windows, and a signed APT repository for Android via Termux.

Security: the settings to check before you connect anything

A personal agent that can run tools and read your messages is powerful, and both projects say so. OpenClaw's README is direct: "Treat inbound messages as untrusted input", and "Tools run on the host for the main session unless you configure sandboxing."

OpenClaw's security guide adds the practical checks:

• Run the audit. `openclaw security audit` reports whether you have drifted from the conservative defaults.
• Keep the Gateway on loopback unless you need more; the guide notes container images "default to an exposed bind", so pair them with authentication.
• Pairing for strangers. Most chat channels answer an unknown direct-message sender with a pairing code instead of processing the message — leave that on.
• Review cross-channel messaging. Agents with message-tool access can send across conversations and channel providers by default; restrict it if that is not what you want.
• One trust boundary per gateway. Users who should not trust each other need separate gateways and credentials.
• Keep bypass flags off in production.

The same principles apply to Hermes or any agent: sandbox tool execution, give it the narrowest accounts and permissions that do the job, and be careful with third-party skills. Our AI agent data-privacy checklist covers the wider questions.

Self-hosting vs managed hosting

Self-hosting means a machine that stays on — a spare computer or a small VPS — plus your model provider's usage charges. Our step-by-step VPS tutorial covers choosing a server, locking it down and keeping the agent running.

Managed hosting trades a monthly fee for someone else running the server. MyClaw describes itself on its pricing page as fully managed cloud hosting for OpenClaw, and also lists Hermes Agent as supported. As of October 2026 the visible plans are:

All plans list auto-updates, daily backups and private instances; Pro, Max and Ultra add priority support and AI credits. The page states that "AI token usage isn't included in the subscription", so budget for model costs separately. The page's search-engine metadata showed lower prices than the visible plan cards when we checked, so confirm the price at checkout.

If you would rather not run an agent framework at all, a hosted agent platform is the third route: MuleRun says on its site that each agent "runs on a dedicated computer that stays on 24/7" and asks for approval before critical actions. Our roundup of the best AI agents of 2026 compares it with other approaches.

Which one should you choose?

• You want your assistant in many chat apps and on your own devices: OpenClaw, with its native apps and 20-plus channels.
• You want an agent that builds up reusable skills and runs on cloud sandboxes: Hermes Agent.
• You want either, without maintaining a server: managed hosting such as MyClaw, with model costs on top.
• You want results rather than a framework: a hosted agent platform.

Both are free, open-source software, so the cheapest way to decide is to install one on a spare machine with a low-risk account and see which fits how you work. For prompting and workflow design that applies to both, see how to prompt AI agents and building an AI agent workflow.

Frequently asked questions

Is OpenClaw free?

Yes. OpenClaw is MIT-licensed and the README says it has "no paid tier, hosted service, or token". You pay for the machine it runs on and for your model provider's usage.

What is the difference between OpenClaw and Hermes Agent?

OpenClaw centres on a local Gateway that keeps state and credentials on your hardware and reaches many chat channels and native apps. Hermes Agent, from Nous Research, centres on a learning loop that creates and improves skills from experience and on running across local, Docker, SSH and serverless backends.

Can I run OpenClaw or Hermes on a VPS?

Yes. Hermes' README mentions running it on a small VPS, and OpenClaw's installer supports Linux. Follow each project's security guidance, especially on exposing the gateway beyond localhost. Our VPS tutorial walks through the setup.

Is OpenClaw owned by OpenAI?

No. The README says OpenClaw is developed by the OpenClaw Foundation, an independent 501(c)(3), and that "OpenAI is a donor, not an owner".

How much does managed OpenClaw hosting cost?

As of October 2026, MyClaw's visible plans run from $29 a month (Lite) to $239 a month (Ultra), with AI token usage billed separately.

Sources checked 23 October 2026: github.com/openclaw/openclaw (README); docs.openclaw.ai/gateway/security; github.com/NousResearch/hermes-agent (README); myclaw.ai/pricing; mulerun.com. Editorial content.