"A media server platform for organizing and streaming content" matching MCP servers:

Enables streaming text-to-speech generation using ElevenLabs with real-time audio playback and voice listing.

A local stdio MCP server that enables validated access to official ElevenLabs APIs with cost controls, local media storage, and audio export for Godot.

Enables local Vietnamese ecommerce copy preparation, source-grounded RAG retrieval, offline voice previews, correction-memory feedback, hook review, and fine-tuning dataset preparation without publishing posts or approving audio.

Enables image and video generation, text-to-speech, and speech-to-text through MCP tools backed by Volcengine Ark Agent Plan.

Enables AI agents to synthesize and play short summaries aloud while keeping full answers on screen, with queued speech and stop control using online natural voices or offline synthesis.

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

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.

Enables text-to-speech synthesis through a streaming, GPU-accelerated gateway, exposing a single tool that returns playable WAV audio with configurable voice and speed.

Enables text-to-speech conversion using ElevenLabs API with voice management, streaming support, and multiple models.

An MCP server that enables text-to-speech generation and phonetic kana conversion using VOICEROID2 via voiceroid_daemon. It supports customizable voice parameters and provides cross-platform audio playback for synthesized speech.

A text-to-speech MCP server that enables AI assistants to speak using the VOICEVOX engine with support for multi-character conversations. It features queue management, low-latency streaming via FFplay, and cross-platform playback across Windows, macOS, and Linux.

Enables natural language-driven speech synthesis using Fish Audio's Text-to-Speech API, supporting multiple voices, streaming, and flexible configuration.

Enables AI agents to use speech AI capabilities including LLM chat completions, text-to-speech in Uzbek, Russian, and English, speech-to-text transcription with speaker labels, voice isolation for noise removal, and realtime WebSocket streaming.

Provides ten hosted audio AI tools — TTS, voice cloning, music generation, stem separation, speaker separation, transcription, denoising, media conversion, and job polling — over a single streamable-HTTP endpoint for any MCP-capable agent.

Enables AI agents to narrate internal thoughts, announce tool actions, and speak final responses aloud through local cross-platform text-to-speech. It exposes dedicated audio tools over stdio JSON-RPC for MCP-compatible clients.

Exposes a single transcribe tool over streamable HTTP so containerised agents can send a media file name and receive text transcribed locally by MacWhisper on the host Mac's GPU, with token-gated access and no uploads or API keys. Callers place media in a configured directory, and the blocking call returns the finished transcript.

Creates short videos for TikTok, Instagram Reels, and YouTube Shorts using the Model Context Protocol (MCP) and a REST API.

Enables authenticated remote access to xAI media generation for images, video, and speech over Streamable HTTP, with persistent media URLs, usage receipts, and enforced daily spend limits.

Enables AI agents and applications to send audio notifications with text-to-speech, message streaming, agent-to-agent conversations, and web push notifications through a persistent message store and MCP integration.

Generates TikTok-style short videos narrated by Peter and Stewie Griffin from any content, using ElevenLabs for voice and FFmpeg for video assembly.

Enables AI clients to convert text into spoken MP3 audio by calling a local voice gateway that renders it with the Eleven v4 model and delivers the result to either a local web playback list or a fixed Telegram chat. It also returns short clips as inline MCP audio content blocks for clients that support embedded playback.

Enables creators to generate short-video voiceover scripts with platform-adapted hooks, key points, and closings, search a golden-quote library, split copy into subtitle lines with estimated timelines, get topic suggestions, and turn a topic into TTS audio plus SRT subtitles in one command. Runs fully locally and offline as part of a Chinese content-creation MCP suite.

Enables AI agents to generate narration in a single fixed, pre-approved voice, returning audio with per-line timing, hashes, and automatic quality checks on content, speaker identity, and pace, all locally and reproducibly.

Enables AI models to generate high-quality voice messages from text using the Piper TTS engine, with automatic model management and audio streaming.

Provides text-to-speech conversion through a unified MCP interface, supporting both local Kokoro and cloud OpenAI TTS engines with streaming audio, voice selection, and customization via natural language instructions.

An MCP server that integrates with Daisys AI platform to enable audio processing tasks, such as recording, transcription, or generation, through natural language commands.

Provides text-to-speech capabilities using Google's Gemini TTS API with support for multiple voices, automatic chunking of long text, multi-speaker dialogue, and audio playback via Windows Media Player.

Enables text-to-speech and speech-to-text through MCP tools, using Groq's free hosted endpoints when configured and falling back to fully local keyless models otherwise. Also provides voice listing and provider health checks.

MCP server that enables AI agents to place real Telegram voice calls and speak a message aloud via TTS, with configurable repeats and call handling.

Enables coding agents to turn explanations of code, pull requests, or concepts into narrated slide walkthroughs voiced locally with Kokoro, returning a link that starts playing in about a second while the remaining slides are still being written. Slides are grounded in real files and git history, checked for errors, and exportable as static folders with captions.