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 xDarkzx · MCP Server · ★ 79
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Audacity-MCP safe to install? View the security audit →
AudacityMCP AI-powered audio editing in Audacity through the Model Context Protocol Quick Start • Why AudacityMCP? • Pipelines • Tool Reference • Troubleshooting AudacityMCP connects any MCP-compatible AI assistant to Audacity, giving it full control over audio editing through 131 tools spanning effects, cleanup, mastering, transcription, and more. Talk to your AI assistant and it edits your audio in real-time. No cloud. No API keys for audio processing. Everything runs locally through Audacity's named pipe interface. Compatibility: AudacityMCP currently works with Audacity 3.x only. Audacity 4.x is not yet supported —
| Stars | 79 |
| Forks | 9 |
| Language | Python |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 71.2196404871915/100 |
| Last Updated | 2026-09-05 |
| Created | 2026-03-14 |
| Platforms | mcp, python |
| Est. Tokens | ~18k |
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Audacity-MCP is AudacityMCP connects any MCP-compatible AI assistant to Audacity, giving it full control over audio editing through 144 tools and 9 pipelines spanning effects, cleanup, mastering, and more. Talk to yo. It is categorized as a MCP Server with 79 GitHub stars.
Audacity-MCP is primarily written in Python. It covers topics such as ai-tools, audacity, audio-processing.
You can find installation instructions and usage details in the Audacity-MCP GitHub repository at github.com/xDarkzx/Audacity-MCP. The project has 79 stars and 9 forks, indicating an active community.
Audacity-MCP is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to Audacity-MCP on Agent Skills Hub include LocalText2Voice, augments-mcp-server, youtube-connector-mcp. 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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