open-vetta — security grade SAFE, quality 65/100

Security audit verdict: SAFE · quality 65/100

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 openvetta · MCP Server · ★ 192

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

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About open-vetta

Open Vetta An open-source desktop AI agent for real work — local-first, extensible, and under your control. English · 简体中文 · Download · Get started · <a href="https

agent-toolsai-agentbyokcoding-agentcross-platformdesktop-appdeveloper-toolselectronharnessknowledge-base

Quick Facts

Stars192
Forks33
LanguageTypeScript
CategoryMCP Server
LicenseApache-2.0
Quality Score65.3899079659922/100
Open Issues5
Last Updated2026-09-20
Created2026-08-03
Platformsmcp, node
Est. Tokens~17k

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Frequently Asked Questions

What is open-vetta?

open-vetta is Open-source, local-first AI agent for coding and real work. BYOK models, MCP, skills, plugins, workflows, and private knowledge bases.. It is categorized as a MCP Server with 192 GitHub stars.

What programming language is open-vetta written in?

open-vetta is primarily written in TypeScript. It covers topics such as agent-tools, ai-agent, byok.

How do I install or use open-vetta?

You can find installation instructions and usage details in the open-vetta GitHub repository at github.com/openvetta/open-vetta. The project has 192 stars and 33 forks, indicating an active community.

What license does open-vetta use?

open-vetta is released under the Apache-2.0 license, making it free to use and modify according to the license terms.

What are the best alternatives to open-vetta?

The top alternatives to open-vetta on Agent Skills Hub include palot, mcp-gearbox, linkly-ai-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

How this security grade is produced

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:

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