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by mbailey · MCP Server · ★ 1.4k
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🔒 Is voicemode safe to install? View the security audit →
VoiceMode Natural voice conversations with Claude Code (and other MCP capable agents) VoiceMode enables natural voice conversations with Claude Code. Voice isn't about replacing typing - it's about being available when typing isn't. Perfect for: Walking to your next meeting Cooking while debugging Giving your eyes a break after hours of screen time Holding a coffee (or a dog) Any moment when your hands or eyes are busy See It In Action Quick Start Requirements: Computer with microphone and speakers Option 1: Claude Code Plugin (Recommended) The fastest way for Claude Code users to get started: Option 2: Python installer package Installs dependencies and the VoiceMode Python package. bash Install UV package manager (if needed
| Stars | 1,365 |
| Forks | 194 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 71.5469776399299/100 |
| Open Issues | 46 |
| Last Updated | 2026-09-15 |
| Created | 2025-06-08 |
| Platforms | claude-code, mcp, python |
| Est. Tokens | ~14k |
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voicemode is Natural voice conversations with Claude Code. It is categorized as a MCP Server with 1.4k GitHub stars.
voicemode is primarily written in Python. It covers topics such as anthropic, asr, claude.
You can find installation instructions and usage details in the voicemode GitHub repository at github.com/mbailey/voicemode. The project has 1.4k stars and 194 forks, indicating an active community.
voicemode is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to voicemode on Agent Skills Hub include Unity-MCP, linkedin-mcp-server, dbhub. 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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