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    Lets AI assistants query available voices from an OpenAI-compatible TTS service and synthesize text into audio with a chosen voice, tone, and speed, returning a public audio URL instead of Base64 data.
    2
    152 npm
    MIT
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    Enables text-to-speech functionality on macOS using the say command, offering extensive control over speech parameters like voice, rate, volume, and pitch for a customizable auditory experience.
    2
    17 npm
    20
    MIT
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    A Node.js server that enables AI assistants to interact with Bouyomi-chan's text-to-speech functionality through Model Context Protocol (MCP), allowing for voice reading of text with adjustable parameters.
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    MIT
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    An enhanced server for ElevenLabs that enables high-quality text-to-speech, voice cloning, and multi-speaker dialogue management. It features advanced conversational tools for transcript retrieval, history tracking, and emotional audio synthesis using the v3 model.
    29
    69 npm
    8
    MIT
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    MCP server for ElevenReader TTS service. Enables document management, URL/ebook upload, voice configuration, and progress tracking.
    17
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    MIT
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    A PowerShell-based MCP server that enables Claude Desktop to convert text to speech using Windows' built-in Speech API, offering features like playback control, speed and volume adjustment.
    10
    MIT
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    This server enables AI models to send SMS messages and initiate Text-to-Speech calls programmatically using ClickSend's API with built-in rate limiting and input validation.
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    MIT
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    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.
    MIT
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    Provides voice summaries after each AI request in Cursor, Cline, or any MCP-supported editor, allowing users to hear what was done and stay informed without staring at the screen.
    9
    MIT
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    Enables AI assistants to convert text to high-quality speech audio using MeloTTS. Automatically splits long texts into segments, generates WAV files, and merges them using ffmpeg with support for multiple languages and customizable speech parameters.
    MIT