"How to list an MCP server on a platform or directory" matching MCP servers:

Text-to-speech MCP server that enables AI assistants to read text aloud on the user's computer using Windows SAPI, with no API key or cloud service required.

Enables converting text to speech audio in 20+ languages, returning base64-encoded MP3 output via Google TTS with x402 micropayment-based pay-per-call access.

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.

Enables conversion of YouTube videos to MP3 format through the Youtube To Mp315 API. Supports checking conversion status, retrieving video titles, and asynchronous video-to-audio conversion with customizable quality and time range settings.

Enables downloading videos from platforms like YouTube and converting them to text using OpenAI Whisper and ffmpeg. It supports multiple output formats including TXT, JSON, SRT, and VTT for transcriptions.

An MCP server that provides speech-to-text transcription and speaker diarization using OpenAI Whisper and pyannote.audio.

An MCP server that enables voice-to-voice AI conversations using ElevenLabs for speech synthesis and recognition, with tools for voice management, text-to-speech, and speech-to-text.

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

Enables users to convert text into high-quality audio by accessing the OpenAI Text-to-Speech API. It supports customizable model selection and voice options for synthesized speech generation via the MCP protocol.

Enables submitting audio via URL or Base64 for local Whisper transcription, then checking job status and results or deleting transcription jobs. It provides asynchronous job handling and SSRF-protected downloads/callbacks without cloud API calls.

Enables MCP-capable chat clients to synthesize speech from text, convert it with a local RVC voice model, and render the result in an inline audio player.

A server that generates MP3 audio files from text using Kokoro TTS technology with optional S3 upload capabilities.

Enables MCP clients such as Claude to generate spoken audio locally, narrating English with Kokoro and Malayalam with IndicF5, Parler-TTS, Piper or MMS, including cloned Malayalam voices, pronunciation lexicons, and number/currency expansion. Outputs loudness-normalised WAV or MP3 and runs long narrations through a pollable job queue so tool calls never time out.

Lets AI assistants render HTML animations to MP4 or GIF in 16:9, 9:16 and 1:1, preview single frames to check their own work, and finish videos with royalty-free music, AI voiceover, burned-in captions, titles and logos. It renders code frame by frame in a real browser rather than generating video from a text prompt.

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.

Generate music with Suno (v5.5) from any MCP client — async, and billed only on successful renders (a failed render auto-refunds). Hosted Streamable-HTTP server; tools generate_song / wait_for_song / check_song.

Enables MCP clients to measure a track's loudness and peak levels, strip artifacts left by AI generators, compare mastering presets, and master single tracks or batches to streaming targets via a hosted remote server or a local stdio bridge. Tracks are supplied as public HTTPS links, with analysis, cleanup and previews free and full masters limited by a daily free quota or credits.

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

An MCP server that lets users generate, edit, and save Xfer Serum 2 presets from plain-English descriptions directly through MCP clients like Claude Code or Claude Desktop, without any separate API keys or LLM calls.

Official MCP server for SpicyAPI, an unrestricted AI API with no platform content filter: browse 200+ image, video, audio and chat models, get exact USD quotes, upload local files, create generation tasks and collect results, with a confirmation before every paid step.

Enables pay-per-call access to 90+ generative AI models and utility tools via any MCP client, with no signup or API key, using wallet-based USDC payments on Base, Tempo, or Solana.

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.

A local MCP server that rings a bell through your speakers to provide audible notifications when AI completes tasks or needs attention.

Enables MCP clients to transcribe local audio files or public audio URLs into plain text, JSON with word timestamps, or SRT/VTT subtitles, with options to save output to a file.

Enables Claude to turn a described beat into a loopclub deep link for auditioning and renting on-chain by encoding track specs into a ?jam= URL and returning an ASCII grid. It also supplies vocabulary, genre examples, and a jam prompt to help generate idiomatic loops.

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.

Enables MCP clients such as Claude Code, Cursor, and VS Code to generate speech through three MiMo TTS models: nine built-in voices (with singing and style/audio tags), voices designed purely from a text description, and voices cloned from a local mp3/wav sample. Audio is streamed and written only inside a sandboxed output directory, with non-overwriting filenames.

Local, private audio transcription MCP server enabling AI agents to transcribe audio files entirely on-device without uploading data.

Enables any MCP client to start, poll, and stop microphone recordings from within a conversation, returning the accumulating transcript on demand. All transcription runs locally on-device, so no audio leaves the machine.

Enables agents to submit audio files to the local Meeting Transcriber macOS app, retrieve diarized transcripts, assign speaker names, and start or stop automatic meeting detection over its localhost automation API. Everything runs on-device, so no audio or transcripts leave the Mac.