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 AI-QL · MCP Server · ★ 1.2k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is tuui safe to install? View the security audit →
TUUI - Local AI Playground with MCP TUUI is a desktop MCP client designed as a tool unitary utility integration, accelerating AI adoption through the Model Context Protocol (MCP) and enabling cross-vendor LLM API orchestration. 📜 Introduction This repository is essentially an LLM chat desktop application based on MCP. It also represents a bold experiment in creating a complete project using AI. Many
| Stars | 1,154 |
| Forks | 108 |
| Language | TypeScript |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 66.1392946511851/100 |
| Open Issues | 2 |
| Last Updated | 2026-05-14 |
| Created | 2025-04-01 |
| Platforms | claude-code, cli, mcp, node |
| Est. Tokens | ~181k |
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tuui is A desktop MCP client designed as a tool unitary utility integration, accelerating AI adoption through the Model Context Protocol (MCP) and enabling cross-vendor LLM API orchestration.. It is categorized as a MCP Server with 1.2k GitHub stars.
tuui is primarily written in TypeScript. It covers topics such as agent, agentic-ai, ai.
You can find installation instructions and usage details in the tuui GitHub repository at github.com/AI-QL/tuui. The project has 1.2k stars and 108 forks, indicating an active community.
tuui is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to tuui on Agent Skills Hub include oreilly-ai-agents, archestra, argo. 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: