"Methods for Acquiring Basic Skills or Abilities" matching MCP servers:

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

MCP server that bridges Ableton Live with AI models, enabling real-time project inspection and control such as track overview, device parameters, and audio analysis.

Enables detection of AI-generated content in images, videos, audio, and text via the AI or Not API. Supports media analysis tools for deepfakes, synthetic voices, and AI-written text.

MCP server for audio transcription using OpenRouter models, supporting verbatim, cleaned, and custom transcription modes.

Enables Claude or any AI agent to operate Live 12 Intro end to end: creating tracks and scenes, writing and quantizing MIDI clips, loading audio onto the Arrangement timeline, setting device parameters in real units, drawing clip automation, mixing with real sidechain, and rendering or analyzing audio so the agent can check its own work. It exposes 57 tools over MCP or a local JSON socket, working within the stock Intro edition's 16-track, 16-scene limits.

MCP server that exposes recorded family stories as read-only tools, enabling Alexa+ to retrieve and deliver voice stories to children through natural language.

Enables ChatGPT to generate ElevenLabs speech from text, returning playable MP3 audio, with voice listing and preference management.

Lets MCP clients search kie.ai's live catalog of 200+ generation models, inspect each model's schema, price and success rate, then prepare, approve and submit media generation plans that return the finished image, video, music or speech files. Paid runs stay behind an explicit prepare → approve → submit flow so credits are only spent once a plan is shown and accepted.

MCP server for SpeechWeave transcription, enabling AI assistants to transcribe local files and URLs via wait-first or async tools.

Render, analyze, and verify audio (WAV or FLAC) through a fully offline, deterministic engine, exposed as MCP tools for AI agents.

Voice input for Claude Code — speak Vietnamese or English; hold a hotkey, speak, release, and the transcribed text is cleaned and pasted into the input box for editing before sending.

Enables MCP-capable assistants to transcribe local audio files or URLs and perform speaker diarization for Spanish and Portuguese audio, with options for speaker count hints, domain prompts, and transcript retrieval in multiple formats.

MCP server integrating VolcEngine for automatic speech recognition (ASR) and text-to-speech (TTS), converting audio to text or text to audio files.

Enables Claude to build and edit multitrack sessions from audio files and synth or drum notes, apply effects, busses and fades, and render mixdowns with loudness measurement, stems, MIDI and session files. It also processes and converts existing audio, and reports format, loudness and waveform details for files or sessions.

Enables AI assistants to transcribe audio files from URLs or local paths using AssemblyAI's services, with support for speaker diarization, language detection, and asynchronous job management through a standardized MCP interface.

An MCP server for controlling Voicemeeter (Basic, Banana, or Potato) on Windows: strip and bus gains, mutes, output routing, live levels, macro buttons, presets, and audio-engine restarts.

Enables AI clients to transcribe YouTube links and uploaded audio or video files, then retrieve the resulting transcripts as text, SRT, VTT, or JSON with timestamps and optional speaker labels. Also supports paging through long transcripts, checking upload progress, listing or deleting jobs, and viewing remaining account minutes.

Exposes the program's push-to-talk transcript history to MCP clients such as Claude Desktop and Claude Code, letting them fetch recent or latest transcripts, query results by time window, range, or ISO timestamp, search text, look up records by id, and read counts, runtime status, or clear history. Each result carries millisecond-precision hold start/end timestamps alongside the transcribed text.

Enables MCP clients to speak by running local voice models using Chatterbox Turbo TTS or Kokoro TTS, with support for voice cloning, paralinguistic tags, and multiple voices.

Enables MCP clients to speak text aloud on macOS using the built-in say command, with no external speech API or keys, and to list available voices and control rate or voice selection. Requests from multiple client threads share a single FIFO playback worker, so speech plays one item at a time and can be inspected, stopped, or muted in hold or discard mode.