"Search for information about 'daw' (Digital Audio Workstation)" matching MCP servers:

Enables headless offline audio processing through MCP tools for rendering stems, analyzing audio and masking, auto-mixing, applying EQ/compression, mastering, comparing references, and running release checks. It works on local audio files without a DAW window, audio interface, GPU, model download, or cloud account.

Enables MCP clients to drive developer workflows through APIs and CLIs, with explicit workspace or trusted-workstation launch modes, bounded command previews, multi-repository rules discovery, and an on-demand skills/recipes entry point. It lets agents review changes, run commands, and load only the smallest relevant rule or skill while reporting evidence and unverified steps.

Editing, analyzing and processing audio files without ffmpeg.

Enables AI agents to build songs by editing a JSON song model: searching a licence-tagged sample library, adding step-pattern and time-stretched loop tracks, setting gain/pan, describing songs, and rendering them to 44.1 kHz WAV/MP3 with release-safety warnings. Songs and renders are read from and written to a project root, so an agent can go from empty project to finished track through MCP tool calls.

A stdio MCP server that controls VMware Workstation via vmrun, enabling VM lifecycle management and snapshot operations.

Enables managing VMs, running guest operations, transferring files, and controlling headless consoles via vmrun, REST, and VNC/RFB through 93 tools.

Audio perception for AI agents. Measure loudness, clipping, noise and pitch; view spectrograms; split audio into events; transcribe speech; compare before/after; and clean up, edit or synthesize sound. Runs locally, no API keys.

Enables AI assistants to query your local browsing history using keyword search, RAG Q&A, and activity stats.

A mock-first MCP server for audio generation that creates placeholder WAV files locally, enabling development and testing of audio workflows without APIs or costs.

Enables batch audio processing and optimization using FFmpeg with preset configurations for game audio, voice processing, and music mastering, including specialized optimization for ElevenLabs AI voice output.

Enables an AI to build, inspect, test, and render logic circuits as .dig files, then open them in the Digital app.

Enables MCP clients to control a running Unreal editor through its local bridge socket, exposing world, blueprint, material, media, vision, pipeline, and status tools. It resolves class names, verifies writes by reading them back, caps ordered pipelines, and reports unreachable or partial results instead of silently succeeding.

Local MCP server for macOS that captures microphone input and/or system audio output into explicit, user-defined sessions and exposes the raw WAV audio to AI agents through MCP tools.

A portable, Dockerized Python tool that implements Model Context Protocol for audio transcription using Whisper models, featuring both CLI and web UI interfaces for converting audio files to JSON transcriptions.

Enables Claude AI to generate professional, production-ready MIDI files (chord progressions, drum patterns, bass lines, melodies, and full arrangements) compatible with any DAW including Logic Pro, Ableton Live, FL Studio, and more.

Enables AI clients to securely inspect and edit approved code, use semantic code intelligence, run builds/tests, supervise bounded processes, inspect Git, and execute owner-approved SSH commands on engineering workstations.

Enables Claude and other AI assistants to interact with your computer's audio system, allowing for recording from microphones and playing audio through speakers.

MCP server that gives AI agents access to current web information through web_search and fetch_url tools, using Tavily, Brave, and DuckDuckGo providers with automatic fallback.

Enables AI-powered music production by integrating with REAPER DAW via MCP protocol, allowing users to control project settings, MIDI editing, and VST plugins through natural language.

Captures and transcribes system audio in real-time using OpenAI Whisper, enabling meeting transcription, content creation, and accessibility through natural language.

An MCP server that masters audio with a professional signal chain using ffmpeg, enabling loudness analysis, vocal-over-beat mixing, full mastering to target LUFS, and Dolby codec export.

An MCP server that lets AI agents search YouTube and YouTube Music, download individual tracks as tagged MP3s with embedded cover art, and list previously downloaded files.

Exposes digital twin device data capabilities as MCP tools, allowing MCP clients to query device status, read real-time metrics, fetch time-series data, and check alerts. Includes a simulated PLC driver with a clean interface for connecting real devices via OPC-UA, Modbus, or gateway APIs.

MCP server that analyzes TTS audio recordings, providing transcription, quality scoring, pacing analysis, and mispronunciation detection to debug voice call center audio.

Enables comprehensive audio file analysis and metadata extraction with specialized game audio development features, supporting batch processing of multiple formats and providing platform-specific optimization recommendations.

Gemini Audio MCP is a high-performance Model Context Protocol (MCP) server that leverages the power of the Gemini 2.0 Multimodal Live API to generate high-fidelity, environmental soundscapes on-demand.

Enables Claude Code to fetch and transcribe YouTube audio stories, validate rewritten scripts, render Vietnamese TTS segments, and assemble a final MP3.

Enables AI models to analyze audio files through numerical fingerprints, pitch tracking, and visual spectrograms without requiring direct audio playback. It provides tools for comparing audio iterations and detecting patterns using token-efficient analysis operations.

Enables an agent to inspect an audio folder and report what is inside each file — duration, sample rate, channels, codec and bitrate — and to group byte-identical files, identical decoded audio stored in different containers, and near-duplicate candidates, with suggested keeps and explicit differences, all read-only.

Enables AI agents to manage macOS audio routing, device switching, volume control, and multi-zone playback.