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 SakuraByteCore · MCP Server · ★ 347
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is codexmate safe to install? View the security audit →
Codex Mate One dashboard for all your local AI coding agents. Switch providers, manage sessions, and orchestrate tasks across Codex, Claude Code, OpenCode, and OpenClaw. Zero cloud, local-first control plane. [Documentation] [Quick Start] [简体中文] [ with a single command.
One manifest for agent skills, MCP servers, and stack profiles across Claude Code, Codex, and Cursor.
Auto-review and iterate until quality work is delivered - a better alternative to ralph-claude-code. Switch be
AI writes code. This automates everything else · 24 plugins · 49 agents · 44 skills · for Claude Code, OpenCod
Local-first macOS app to browse, search, analyze, and resume supported AI coding-agent session history across
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codexmate is One dashboard for all your local AI coding agents. Switch providers, manage sessions, and orchestrate tasks across Codex, Claude Code, Gemini CLI, CodeBuddy Code, Pi, OpenCode, KiloCode, and OpenClaw.. It is categorized as a MCP Server with 347 GitHub stars.
codexmate is primarily written in JavaScript. It covers topics such as ai, ai-tools, claude-code.
You can find installation instructions and usage details in the codexmate GitHub repository at github.com/SakuraByteCore/codexmate. The project has 347 stars and 35 forks, indicating an active community.
codexmate is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to codexmate on Agent Skills Hub include OpenContext, claude-code-config-switcher, agent-starter. 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.
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