No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by browserable · Agent Tool · ★ 1.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is browserable safe to install? View the security audit →
Website Twitter Open source browser automation library for AI agents Browserable allows you to build browser agents that can navigate sites, fill out forms, clicking buttons and extract information. It is currently at 90.4% on the Web Voyager benchmarks. Quick start The fastest way to get started is to run the npx command. This will guide you through the setup process and ensure you have all required dependencies. Visit to set your LLM and Remote Browser API Keys to start using. Manual setup Clone the repository: Pre-requisites: Install Docker Install Docker Compose Start the development environment: Set your API keys: Open Browserable admin dashboard: [http://localhost:2001/dash/@admin/settings](http://localhost:2001/dash/@admin
| Stars | 1,208 |
| Forks | 104 |
| Language | JavaScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 70.0612153286231/100 |
| Open Issues | 9 |
| Last Updated | 2025-08-27 |
| Created | 2025-04-07 |
| Platforms | browser, node |
| Est. Tokens | ~560k |
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browserable is Open source and self-hostable browser automation library for AI agents. It is categorized as a Agent Tool with 1.2k GitHub stars.
browserable is primarily written in JavaScript. It covers topics such as ai-agents, ai-tools, browser-automation.
You can find installation instructions and usage details in the browserable GitHub repository at github.com/browserable/browserable. The project has 1.2k stars and 104 forks, indicating an active community.
browserable is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to browserable on Agent Skills Hub include browsernode, web-agent-protocol, Interceptor. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: