"Information about Supabase" matching MCP servers:

An MCP server for OBS Studio that subscribes to events and maintains a history, enabling queries about audio levels, source states, and past actions rather than only one-shot requests.

An MCP server that enables AI assistants to search, analyze, and retrieve information about audio samples from Freesound.org through their API.

A powerful MCP tool for parsing and manipulating MIDI files that allows users to read, analyze, and modify MIDI files through natural language commands, supporting operations like reading file information, modifying tracks, adding notes, and setting tempo.

An MCP server for parsing and analyzing Ableton Live .als project files offline, enabling queries about tempo, tracks, clips, and MIDI data through tools like als_summary and als_list_tracks.

Enables searching and downloading audio samples from Freesound using keywords, filters, and sound IDs. It provides detailed sound metadata including duration, license information, and preview URLs.

A Model Context Protocol server that integrates with VOICEVOX engine to provide text-to-speech synthesis and speaker information retrieval, allowing users to generate and play voice audio from text.

Enables AI agents to enroll and verify voice samples against known identities, providing honest confidence signals about voice authenticity.

Connects AI coding agents to PreSonus StudioLive III mixers over the local network, exposing live mixer context such as channel names, mute/solo/fader state, Fat Channel compressor/EQ models, and meter activity as MCP resources and tools for reading and reasoning about live sound engineering.

Integrates with Freesound.org to enable searching, discovering, and previewing audio content such as sound effects and music loops. It provides detailed metadata and licensing information to support video editing and content creation workflows.

Provides voice recognition and text extraction capabilities with support for both stdio and MCP modes, processing audio files or base64 encoded data and returning structured results with language, emotion, and speaker information.

Enables asking questions about image, audio, or video files using state-of-the-art multimodal models. Powered by fal.ai for advanced media analysis and understanding capabilities.

Enables text-only AI agents to ask questions about images, audio, and video by passing file paths or URLs to a multimodal model and returning text answers.

Enables transcription of audio files using Google Gemini AI and creates a searchable knowledge base, allowing users to ask natural language questions about content in meetings, podcasts, lectures, and other audio recordings.