OpenClaw: review, pricing, security and alternatives

What OpenClaw does

OpenClaw belongs to the personal assistants family: general-purpose agents, often self-hosted and driven from a messaging app, that act for you on your files, accounts and services. On our grid it ranks #1 of the 46 projects of this family listed in the directory.

You use it from: terminal (CLI), web app, and messaging (Telegram, Slack, WhatsApp…). Usable models: Claude (Anthropic), GPT (OpenAI), Gemini (Google), local models (Ollama, llama.cpp, vLLM…), and OpenRouter. It can run on your own machine or server.

Who is OpenClaw for?

It targets individuals and freelancers who want an assistant able to act for them day to day, often from a messaging app. Typical tasks people give it:

• sort e-mail and draft replies
• manage a calendar and reminders
• look up information and summarise it
• run small recurring tasks

It is a good candidate if you want to talk to it from your usual messaging app, without opening another app, you are comfortable in a terminal, your data must stay on your machines, and you want the option of a local model, with no API fees.

Access and human control

According to its documentation, OpenClaw can:

• run commands in a terminal
• read and edit files
• drive a web browser
• call online services and APIs
• read and send messages

We could not establish whether it asks for human approval before sensitive actions: test it first on an unimportant account or folder.

OpenClaw pricing

The code is free, under the MIT licence.

Getting started with OpenClaw

1. Install it: the project ships as a Node.js package (install with npm, or run directly with npx). The exact command is in the repository README.
2. Pick the model: an API key from a provider, or a local model if your machine has enough graphics memory (the VRAM calculator tells you).
3. Give it a first playground with nothing at stake: a test folder, a secondary account or a throwaway project. Only open your real accounts once you have seen how it behaves.
4. Give it a short, checkable task, review the result and its action log, then raise the difficulty step by step.

Security: risk level

A personal assistant often combines access to private data, reading outside content and sending messages: the combination that enables data leaks through prompt injection.

Points found for OpenClaw:

• Sensitive access: it can run commands in a terminal, with no established default human approval.
• Trifecta: access to private data, reading outside content and sending messages. That combination makes data leaks through prompt injection possible.

Three habits: least privilege (minimal rights, dedicated keys), human approval for irreversible actions, a sandbox for code execution. The AI agent security check reviews your setup in a few minutes.

Project activity and releases

Created on November 24, 2025, the openclaw/openclaw repository has 392,941 stars, 82,591 forks and 5,000 open issues, with 118,504 commits in total. It received changes this month.

Over the last 52 weeks: 125,376 commits, an average of 2,411.1 per week.

271 releases in total; 20 in the last twelve months. Latest release: v2026.10.7, on October 24, 2026.

OpenClaw vs other personal assistants

GitHub stars of the best-rated open-source projects in the personal assistants family. Stars measure attention, not quality: a heavily promoted project collects them fast, a specialised tool will have few.

OpenClaw and other personal assistants at a glance

The 7 best-ranked agents in the same family, 7 of them open source. The score out of 100 only applies to open-source projects; for proprietary services we show the published entry price. A dash marks information the documentation does not state.

How we rated it

Score: 95/100, computed only from public, verifiable data, with no subjective testing or partnership:

• Adoption 40/40: 392,941 stars on a log scale (40 points from about 200,000).
• Activity 30/30: last commit less than a month ago, 20 releases in six months, 125,376 commits in a year.
• Framework 25/30: licence, default human approval, self-hosting, model choice and documentation site.

The score does not say whether the agent will succeed at your tasks: it measures how solid the project is. The full grid is on the method page.