Risuai: Make your own story. User-friendly software for LLM roleplaying

by kwaroran · MCP Server · ★ 1.8k

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

Security audit verdict: SAFE · quality 63/100

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. Full audit →

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.

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Quick Facts

Stars1,773
Forks363
LanguageTypeScript
CategoryMCP Server
LicenseGPL-3.0
Quality Score63/100
Open Issues191
Last Updated2026-11-04
Created2023-04-12
Platformsclaude-code, cli, gemini, mcp, node
Est. Tokens~14k

About Risuai

Risuai Risuai, or Risu for short, is a cross platform AI chatting software / web application with powerful features such as multiple API support, assets in the chat, regex functions and much more. Screenshots [screenshot1]: https://github.com/kwaroran/Risuai/assets/116663078/cccb9b33-5dbd-47d7-9c85-61464790aafe [screenshot2]:...

Risuai alternative? Top 6 similar tools

Looking for a Risuai alternative? If you're comparing Risuai 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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    Production-ready AI chat. Start here and make it your own.

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    Lemonade helps users discover and run local AI apps by serving optimized LLMs right from their own GPUs and NP

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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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