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 Kochava-Studios · MCP Server · ★ 2.0k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is witsy safe to install? View the security audit →
Witsy Desktop AI AssistantUniversal MCP Client Downloads Download Witsy from the releases page. On macOS you can also . What is Witsy? Witsy is a BYOK (Bring Your Own Keys) AI application: it means you need to have API keys for the LLM providers you want to use. Alternatively, you can use Ollama to run models locally on your machine for free and use them in Witsy. It is the first of
| Stars | 2,027 |
| Forks | 171 |
| Language | TypeScript |
| Category | MCP Server |
| License | AGPL-3.0 |
| Quality Score | 61.6906108498955/100 |
| Open Issues | 60 |
| Last Updated | 2026-04-23 |
| Created | 2024-04-25 |
| Platforms | cli, gemini, mcp, node |
| Est. Tokens | ~2054k |
Looking for a witsy alternative? If you're comparing witsy 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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witsy is Witsy: desktop AI assistant / universal MCP client. It is categorized as a MCP Server with 2.0k GitHub stars.
witsy is primarily written in TypeScript. It covers topics such as anthropic, deepseek, electron-app.
You can find installation instructions and usage details in the witsy GitHub repository at github.com/Kochava-Studios/witsy. The project has 2.0k stars and 171 forks, indicating an active community.
witsy is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to witsy on Agent Skills Hub include codecompanion.nvim, sdk-python, agentops. 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: