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 google-americas · MCP Server · ★ 52
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is way-back-home safe to install? View the security audit →
# 🚀 Way Back Home An immersive AI workshop platform where participants learn to build intelligent agents while rescuing a stranded space explorer. Way Back Home is a hands-on workshop experience that teaches Google Cloud AI technologies through an engaging narrative. Participants crash-land on an alien planet and must use AI to identify themselves, analyze their surroundings, and coordinate rescue efforts. [](https://codelabs.developers.google.com/way-back-home-level-5/instructions
| Stars | 52 |
| Forks | 34 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 63.7644781884515/100 |
| Open Issues | 1 |
| Last Updated | 2026-03-20 |
| Created | 2025-12-26 |
| Platforms | mcp, python |
| Est. Tokens | ~7184k |
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🚀 Way Back Home
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way-back-home is 🚀 Way Back Home. It is categorized as a MCP Server with 52 GitHub stars.
way-back-home is primarily written in Python. It covers topics such as a2a, adk, agents.
You can find installation instructions and usage details in the way-back-home GitHub repository at github.com/google-americas/way-back-home. The project has 52 stars and 34 forks, indicating an active community.
way-back-home is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to way-back-home on Agent Skills Hub include way-back-home, lucid-agents, agent-kernel. 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: