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 bytebot-ai · MCP Server · ★ 11.1k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is bytebot safe to install? View the security audit →
Bytebot: Open-Source AI Desktop Agent An AI that has its own computer to complete tasks for you 🌐 Website • 📚 Documentation • 💬 Discord • 𝕏 Twitter Deutsch | Español | français | 日本語 | 한국어 | Português | [Русский](https://zdoc.app/ru/bytebot-ai/bytebo
| Stars | 11,084 |
| Forks | 1,519 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 72.6910030115627/100 |
| Open Issues | 72 |
| Last Updated | 2025-09-12 |
| Created | 2025-02-03 |
| Platforms | docker, gemini, mcp, node |
| Est. Tokens | ~1283k |
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bytebot is Bytebot is a self-hosted AI desktop agent that automates computer tasks through natural language commands, operating within a containerized Linux desktop environment.. It is categorized as a MCP Server with 11.1k GitHub stars.
bytebot is primarily written in TypeScript. It covers topics such as agent, agentic-ai, agents.
You can find installation instructions and usage details in the bytebot GitHub repository at github.com/bytebot-ai/bytebot. The project has 11.1k stars and 1519 forks, indicating an active community.
bytebot is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to bytebot on Agent Skills Hub include AstrBot, cursor-talk-to-figma-mcp, sdk-python. 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: