AudacityMCP
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- AlicenseBqualityAmaintenanceConnects any MCP-compatible AI assistant to Audacity, providing 132 tools for real-time audio editing, cleanup, mastering, and transcription — all running locally without cloud dependencies.100Apache 2.0
- AlicenseNot gradedqualityDmaintenanceEnables LLM-driven audio pipelines by controlling Audacity through mod-script-pipe, allowing generative audio, effects, and export via MCP tool calls.MIT
- AlicenseAqualityAmaintenanceEnables MCP-compatible AI assistants to control Audacity 4 locally for audio editing, effects, VST3 plugins, and cleanup pipelines via a TCP JSON-RPC bridge, with no cloud or API keys.1562Apache 2.0
- FlicenseNot gradedqualityDmaintenanceEnables AI assistants to programmatically edit, analyze, and export audio projects through MCP tools, including multi-track editing, effects, transcription, and semantic search.1-
- FlicenseNot gradedqualityCmaintenanceEnables Claude to analyze and repair audio files by viewing spectrograms, measuring noise, and applying fixes like healing hums or isolating speakers, all with undoable operations and without uploading audio.-
- AlicenseBqualityDmaintenanceEnables advanced audio transcription, text-to-speech generation, and audio processing using OpenAI's Whisper and GPT-4o models with support for multiple audio formats, file management, and parallel processing.821 PyPI60MIT
TDQS
Scored across 144 tools
Most tools are clearly distinct (project_, track_, label_, effect_ prefixes group by domain). However, there is notable redundancy and overlap: label_delete_audio_at vs label_cut_regions vs label_delete_regions vs label_split_regions vs label_silence_regions all operate on labeled regions with similar purposes. Similarly, cursor_to_track_end and select_cursor_to_track_end, and multiple label export functions (label_export, label_export_audio_segments, project_export_labels) create ambiguity about which to select.
The naming follows a consistent verb_noun or category_verb pattern (project_, track_, label_, effect_, edit_, select_, cursor_, transport_, generate_, auto_). There are a few inconsistencies like 'normalize' and 'compressor' and 'limiter' and 'click_removal' that lack the effect_ prefix used by sibling tools, and 'get_noise_profile'/'noise_reduction' deviate from the pattern, but overall the convention is strong and predictable.
144 tools is an extreme number for an audio editor MCP server. While Audacity is feature-rich, this surface is far beyond what agents can reasonably navigate. Many tools could be consolidated (e.g., the seven separate auto_cleanup_* pipelines, the large effect_* family, and the transcription set). This count will cause selection difficulty and cognitive overload for any agent.
The surface is quite comprehensive, covering project lifecycle (new/open/save/close/import/export), track management, selection, transport, editing, effects, generation, analysis, labeling, noise reduction, pipelines, and transcription. Minor gaps exist (no explicit record control for a specific track, no envelope editing beyond metadata, no undo/redo tools), but overall the domain is well covered for a full audio editing workflow.