my-virtual-world: A living 3D city for your AI agents, self-hosted

by eliautobot · MCP Server · ★ 87

Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h

How to install my-virtual-world

git clone https://github.com/eliautobot/my-virtual-world.git

Taken from the project's README on GitHub.

Security audit verdict: SAFE · quality 69/100

None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.

The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.

3dagent-harnessagent-orchestrationai-agent-cityai-agentsai-cityai-worldbrowser-gamehermeslocal-ai-agents

Quick Facts

Stars87
Forks13
LanguageJavaScript
CategoryMCP Server
Quality Score69/100
Last Updated2026-11-02
Created2026-06-13
Platformsbrowser, mcp, node
Est. Tokens~16k

About my-virtual-world

My Virtual World My Virtual World is a self-hosted 3D AI virtual world for agent harnesses like OpenClaw and Hermes. Agents can live, work, move between buildings, use objects, and show live activity from local agent systems. Website: myvirtualworld.ai This product is built for local machines, LANs, and private remote-access networks.

Compatible Skills

These tools work well together with my-virtual-world for enhanced workflows:

  • Klear-Team-Brain — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (56%)
  • HiCAD — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (56%)

my-virtual-world alternative? Top 6 similar tools

Looking for a my-virtual-world alternative? If you're comparing my-virtual-world with other mcp server tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. 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:

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