Audacity MCP

AudacityMCP

AI-powered audio editing in Audacity through the Model Context Protocol

Quick Start • Why AudacityMCP? • Pipelines • Tool Reference • Troubleshooting

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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 — we hope to add support in the future.

Works With

AudacityMCP works with any AI client that supports the Model Context Protocol:

• Claude Desktop — Anthropic's desktop app
• Claude Code — CLI agent
• Cursor — AI code editor with MCP support
• Any other MCP-compatible client

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Quick Start

1. Get AudacityMCP

Option A: Click the green Code button above → Download ZIP → extract to a folder

Option B: Clone with git:

git clone https://github.com/xDarkzx/Audacity-MCP.git

2. Run the installer (sets up everything else automatically)

Open the folder and run:

• Windows: Double-click install.bat
• macOS / Linux: Open terminal in the folder and run bash install.sh

> The installer does 3 things: installs audacity-mcp from PyPI, enables mod-script-pipe in Audacity, and configures Claude Desktop — no manual JSON editing needed.

Other MCP clients (Cursor, Claude Code, etc.)

If you're not using Claude Desktop, install manually with pip install audacity-mcp and add to your client's MCP config:

{
  "mcpServers": {
    "audacity": {
      "command": "audacity-mcp"
    }
  }
}

Check your client's MCP documentation for the config file location.

3. Start editing

Open Audacity, load some audio, then talk to your AI:

"Clean up this podcast recording"
"Master this track for Spotify, it's EDM"
"Transcribe this and add labels at each sentence"
"Add reverb with a large room, then export as FLAC"

> Audacity must be open first. AudacityMCP communicates through Audacity's named pipe — it can't launch Audacity for you.

> See the full [Installation Guide](docs/INSTALLATION.md) for detailed setup on all platforms and MCP clients.

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Why AudacityMCP?

Without AudacityMCP: You manually navigate menus, tweak effect parameters by ear, apply effects one at a time, look up ACX specs, and repeat until it sounds right.

With AudacityMCP: You describe what you want in plain English and the AI handles the rest — picking the right effects, setting industry-standard parameters, and chaining operations together.

| | Manual Audacity | With AudacityMCP | |---|---|---| | Podcast cleanup | 5+ steps across different menus, guessing compressor settings | "Clean up this podcast" — one sentence | | Music mastering | Research genre-appropriate EQ/compression, apply each manually | "Master this for Spotify, it's hip-hop" — genre-tuned presets | | Noise removal | Effect → Noise Reduction → Get Profile → select all → apply | "Remove the background noise" — automatic profiling | | Batch operations | Repetitive menu navigation for each operation | Describe the full chain and watch it happen | | Transcription | Export audio, use external tool, import results back | "Transcribe this and add labels" — stays in Audacity | | Learning curve | Know which effects exist and what parameters to use | Just describe the result you want |

AudacityMCP is especially useful for:

• Podcasters who want consistent, professional sound without audio engineering knowledge
• Musicians who need quick mastering with genre-appropriate settings
• Content creators working with interviews, voiceovers, or field recordings
• Anyone who'd rather describe what they want than click through menus

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What Can It Do?

You:  "Clean up this podcast recording"
AI:   Runs auto_cleanup_podcast → HPF 80Hz → noise reduction → compression → safe loudness check

You:  "Master this track for Spotify, it's EDM"
AI:   Runs auto_master_music style=edm → HPF 30Hz → click removal → compression 2.5:1 → bass +2dB → loudness check

You:  "This is a noisy live recording, fix it up"
AI:   Runs auto_cleanup_live → HPF 100Hz → click removal → noise reduction 18dB → compression 5:1

You:  "Transcribe this interview and add labels"
AI:   Runs transcribe_to_labels → faster-whisper transcription → Audacity labels at each timestamp

You:  "Add reverb to the vocals, then export as FLAC"
AI:   select region → reverb effect → export to FLAC

Features

131 Tools Across 11 Categories

| Category | Tools | Highlights | |----------|-------|------------| | Effects | 30 | Reverb, echo, pitch shift, tempo change, EQ, phaser, distortion, paulstretch, HPF/LPF, bass & treble, tremolo, wahwah | | Cleanup & Mastering | 18 | Noise reduction, compressor, limiter, 9 one-click pipelines, analysis tool | | Editing | 13 | Cut, copy, paste, split, join, trim, silence, duplicate, undo, redo | | Project | 12 | New, open, save, import/export (WAV, MP3, FLAC, OGG, AIFF) | | Track | 15 | Add mono/stereo, remove, set properties, mix & render, mute/solo, pan, volume | | Selection | 12 | Select all/none/region/tracks, zero crossing, cursor positioning | | Transport | 7 | Play, stop, pause, record, play region, get position | | Analysis | 6 | Contrast, clipping detection, spectrum, beat finder, sound labeling | | Generation | 5 | Tone, noise, chirp, DTMF, rhythm track | | Transcription (Experimental) | 7 | Full/selection transcribe, to labels, to SRT/VTT/TXT, model preload | | Labels | 6 | Add, add at time, get all, edit, import/export |

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Pipelines

AudacityMCP includes 9 one-click pipelines for common audio tasks. Each pipeline is designed to be safe for badly recorded audio — it will never boost your audio dangerously. Pipelines clean up and improve your audio, then you can manually adjust loudness afterward if needed.

How Pipelines Work

1. You tell the AI what you want (e.g. "clean up this podcast")
2. The AI picks the right pipeline and starts it
3. The pipeline runs in the background — you get a job_id back
4. Poll with check_pipeline_status every 15-30 seconds to monitor progress
5. When done, a popup appears in Audacity

> Safety rule: Pipelines only reduce peaks if they're too hot. They never boost loudness. If you want to hit a specific LUFS target (e.g. -14 for Spotify), ask the AI to run loudness_normalize after you've checked the results look good.

Pipeline Reference

auto_analyze_audio — Analyze before processing

Measures your audio and recommends the best pipeline. Run this first if you're not sure what to do.

You: "Analyze this audio"
→ Returns: peak level, noise floor, clipping status, recommended pipeline

auto_cleanup_audio — Safe cleanup only

Cleans up noise and artifacts without changing loudness at all. Use when levels are already fine.

You: "Just clean up the noise, don't change the volume"
→ DC offset removal → HPF 80Hz → noise reduction → click removal (optional)

auto_cleanup_podcast — Podcast / voiceover

Professional broadcast processing for spoken word.

You: "Clean up this podcast recording"
→ DC offset → HPF 80Hz → noise reduction 12dB → compression 3:1 → safe loudness check

auto_audiobook_mastering — Audiobook (ACX/Audible)

Targets ACX requirements for audiobook distribution.

You: "Master this for ACX / Audible"
→ DC offset → HPF 80Hz → noise reduction 12dB → compression 2.5:1 → safe loudness check → peak cap -3dB

auto_cleanup_interview — Interview / dialogue

Light touch for conversations — preserves natural dynamics.

You: "Clean up this interview recording"
→ DC offset → HPF 80Hz → noise reduction 8dB → compression 2.5:1 → safe loudness check

auto_cleanup_vocal — Singing / studio vocal

Tuned for vocal recordings with presence EQ for clarity.

You: "Process this vocal recording"
→ DC offset → HPF 100Hz → noise reduction 10dB → compression 3:1 → presence EQ (+3dB treble, -1dB bass) → safe loudness check

auto_cleanup_live — Live / field / noisy recording

Aggressive cleanup for noisy environments. First 0.5s must be ambient noise for profiling.

You: "This is a noisy live recording, clean it up"
→ DC offset → HPF 100Hz → click removal → noise reduction 18dB → compression 5:1 → safe loudness check

auto_master_music — Music mastering

Genre-tuned mastering with 6 presets: edm, hiphop, rock, pop, classical, acoustic.

You: "Master this hip-hop track"
→ HPF 30Hz → click removal → compression 2:1 → bass +3dB treble +1dB → safe loudness check

You: "Master this for a classical album"
→ HPF 30Hz → click removal → compression 1.3:1 (very gentle) → no EQ → safe loudness check

| Preset | HPF | Compression | Bass EQ | Treble EQ | |--------|-----|-------------|---------|-----------| | EDM | 30 Hz | 2.5:1 / 80ms | +2 dB | +1 dB | | Hip-Hop | 30 Hz | 2:1 / 100ms | +3 dB | +1 dB | | Rock | 40 Hz | 2:1 / 100ms | 0 dB | +1 dB | | Pop | 35 Hz | 2:1 / 80ms | +1 dB | +1.5 dB | | Classical | 30 Hz | 1.3:1 / 200ms | 0 dB | 0 dB | | Acoustic | 30 Hz | 1.5:1 / 150ms | 0 dB | 0 dB |

auto_lofi_effect — Creative lo-fi / vintage

Apply a warm, vintage lo-fi sound. Presets: light, medium, heavy.

You: "Give this a lo-fi vibe"
→ HPF → LPF (muffled highs) → bass/treble warmth → compression 2:1 → safe loudness check

After a Pipeline: Adjusting Loudness

Pipelines intentionally leave loudness alone (they only reduce if peaks are clipping). To hit a streaming target:

You: "Now normalize this to -14 LUFS for Spotify"
→ AI uses loudness_normalize tool with lufs_level=-14

You: "Normalize to -16 LUFS for podcast"
→ AI uses loudness_normalize tool with lufs_level=-16

> Why not do this automatically? LUFS normalization can boost quiet/badly recorded audio by 10-20 dB, which blows it out. By separating cleanup from loudness, you get to check the results before the final loudness step.

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Local Transcription (Experimental)

> This feature is experimental and requires separate setup. Everything else works without it.

Powered by faster-whisper — runs entirely offline, your audio never leaves your machine:

• 5 model sizes: tiny, base, small, medium, large-v3
• Transcribe full audio or just a selection
• Export as SRT, VTT, or plain text subtitles
• Auto-add Audacity labels at each spoken segment
• Language detection or specify 99+ languages

> Setup required before first use: See [Transcription Setup](docs/INSTALLATION.md#transcription-setup-optional) for installation steps.

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What's New — v0.1.3

32 new tools (99 → 131), pipeline tuning fixes, and live-tested against Audacity.

• New effects: Reverse, Invert, Repair, AutoDuck, NotchFilter, VocalReduction, AdjustableFade, StudioFadeOut, CrossfadeClips, CrossfadeTracks, ClipFix, SlidingStretch, Tremolo
• New editing: Split (in place), SplitCut, SplitDelete, Disjoin + renamed old split → edit_split_new
• New tracks: StereoToMono, MixAndRenderToNew, MuteAll, UnmuteAll, Resample, AlignEndToEnd, AddLabelTrack
• New selection: CursorToTrackStart/End, CursorToProjectStart/End, SelectCursorToTrackEnd
• New project: EditMetadata, ImportMIDI
• New labels: RegularIntervalLabels
• Pipeline fixes: ACX peak cap -3.0→-3.5dB, live NR 18→12dB, podcast comp 10ms/1s→30ms/200ms, interview release 1s→200ms
• Bug fix: effect_repair now uses long timeout (Audacity shows popup on invalid selection)
• Validation: Added missing range checks on AutoDuck, VocalReduction, SlidingStretch, Resample

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Troubleshooting

mod-script-pipe Not Enabled

The installer enables this automatically, but if it didn't work (e.g. Audacity was never opened before), enable it manually:

1. Open Audacity
2. Go to Edit → Preferences (Windows/Linux) or Audacity → Preferences (macOS)
3. Click Modules in the left sidebar
4. Set mod-script-pipe to Enabled
5. Click OK and restart Audacity

Connection Issues

| Problem | Fix | |---------|-----| | "Pipe not found" | Open Audacity first. Make sure mod-script-pipe is enabled (see above). Restart Audacity after enabling. | | "Pipe timeout" | Audacity is busy. Wait for it to finish — some effects take minutes on long files. | | Connection works once then fails | The pipe disconnected (Audacity crash or restart). Just try again — AudacityMCP auto-reconnects. | | "Access denied" (Windows) | Audacity and your AI client must run as the same user. Don't mix admin and non-admin. |

Pipeline Issues

| Problem | Fix | |---------|-----| | Pipeline blows out / clips the audio | This shouldn't happen anymore — pipelines only reduce peaks, never boost. If it does, undo (Ctrl+Z) and report the issue. | | "A pipeline is already running" | Only one pipeline can run at a time. Use check_pipeline_status with your job_id to monitor the current one. | | Pipeline finishes but audio is too quiet | That's by design — pipelines don't boost. Ask the AI: "Normalize to -14 LUFS" after checking results. | | Noise reduction sounds metallic/warbled | The first 0.5 seconds of your track must be pure silence/room noise for profiling. If it's not, trim to add silence or use auto_cleanup_audio with remove_noise=False. | | Pipeline step failed (in warnings) | Individual steps can fail without stopping the pipeline. Check the warnings field in check_pipeline_status for details. |

Audio Quality Tips

| Want | Do This | |------|---------| | Remove background noise | Make sure the first 0.5s of your track is pure room tone (no speech/music). The pipeline uses this to build a noise profile. | | Fix clipping | Run auto_analyze_audio first. If it detects clipping, use auto_cleanup_audio before other pipelines. | | Hit -14 LUFS for Spotify | Run a cleanup pipeline first, check the results look good, then ask the AI to apply loudness_normalize at -14 LUFS. | | Hit -16 LUFS for podcast | Same approach — cleanup first, LUFS second. | | ACX audiobook compliance | Use auto_audiobook_mastering. It targets RMS -20 dB with a -3.5 dB peak cap (safety margin). | | Quick cleanup without changing volume | Use auto_cleanup_audio — it only removes noise and artifacts, no loudness changes. |

General Issues

| Problem | Fix | |---------|-----| | "No module named faster_whisper" | Run pip install faster-whisper. Transcription is optional — everything else works without it. | | Model download fails | Check internet and retry. Models cache locally after first download. | | Pipes missing in /tmp (macOS/Linux) | Check Audacity is running and mod-script-pipe is enabled. Check Audacity's console for errors. |

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Architecture

┌──────────────┐     stdio      ┌──────────────┐   named pipe   ┌──────────────┐
│  MCP Client  │◄──────────────►│ AudacityMCP  │◄──────────────►│   Audacity   │
│(AI assistant)│    (JSON-RPC)  │   FastMCP    │  (commands)    │              │
└──────────────┘                └──────────────┘                └──────────────┘
                                       │
                                       ├── audacity_mcp/main.py          (entry point)
                                       ├── audacity_mcp/audacity_client.py (pipe I/O)

…

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [xDarkzx](https://github.com/xDarkzx)
- **Source:** [xDarkzx/Audacity-MCP](https://github.com/xDarkzx/Audacity-MCP)
- **License:** Apache-2.0

Install and usage instructions live in the source repository linked above.