Audacity-MCP: Claude AI Integration for Local Audio Editing with 131 Tools
Direct Claude-to-Audacity Integration
Audacity-MCP is a free, open-source tool that connects Claude AI to Audacity through the pipe interface. You describe what you want done to your audio, and Claude executes the actual effects in Audacity.
Key Features from Source
- 131 tools covering effects, editing, mixing, mastering, and analysis
- 9 automated pipelines for common workflows: podcast, audiobook/ACX, interview, live recording, and music mastering by genre
- Local transcription with Whisper — no API keys, no cloud processing, runs on your machine
- Works with Claude Desktop, Claude Code, or Cursor
- Built with Claude Code — Claude helped write and test the tools against live Audacity
Example Commands
"clean up this podcast recording"→ executes noise reduction, compression, and loudness check"master this for spotify, its EDM"→ runs genre-tuned mastering pipeline"transcribe this and export as SRT"→ performs local Whisper transcription with timestamps"reverse the selection and add a fade out"→ direct effect control
Workflow Examples
For "remove the background noise and get this ready for my podcast," the tool runs the full chain: noise profile, reduction, compression, loudness check. For "master this EDM track," it picks the right HPF, compression ratio, and EQ for the genre.
📖 Read the full source: r/ClaudeAI
👀 See Also
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Ninetails Memory Engine V4.5: Int8 Quantization + LRU Cache Cuts Local MCP Memory to 60MB
The Ninetails Memory Engine V4.5 uses Int8 scalar quantization and LRU cache eviction to reduce vector storage from 6KB to 1.5KB per embedding, keeping the entire engine at 40-60MB RAM. It combines 70% vector similarity with 30% BM25 search in a fully local SQLite implementation.
vllm-mlx fork adds tool calling and prompt cache for local AI coding agents
A developer has modified vllm-mlx to fix tool calling issues and add prompt caching, reducing TTFT from 28s to 0.3s for OpenClaw on Apple Silicon. The fork supports Qwen3-Coder-Next at 65 tok/s on M3 Ultra with working function calling.
OmniCoder-9B: 9B Parameter Coding Agent Fine-Tuned on 425K Agentic Trajectories
Tesslate released OmniCoder-9B, a 9-billion parameter coding agent model fine-tuned on Qwen3.5-9B's hybrid architecture. It was trained on 425,000+ curated agentic coding trajectories from Claude Opus 4.6, GPT-5.4, GPT-5.3-Codex, and Gemini 3.1 Pro.