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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.
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    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.
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    MIT
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    A text-to-speech MCP server with 48 voices across 9 languages, supporting emotion spans, SFX tags, and multi-speaker dialogue. Deployable via a single npx command with built-in guardrails and swappable backends.
    MIT
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    Local-first speech-to-text and text-to-speech MCP server. Hot-swappable engines via config.yaml — no code changes, no API keys required.
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    MIT
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    A Model Context Protocol server that integrates high-quality text-to-speech capabilities with Claude Desktop and other MCP-compatible clients, supporting multiple voice options and audio formats.
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    An MCP server that lets AI assistants send spoken audio notifications using high-quality AI voices, so you don't have to stare at the screen waiting for long tasks to finish.
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    Provides text-to-speech and Telegram notification capabilities via the Model Context Protocol. Supports multiple TTS providers and Telegram messaging with optional setup web interface.
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    MIT
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    Provides speech recognition (STT) and synthesis (TTS) tools via the Sber SaluteSpeech API, enabling audio transcription and voice generation through natural language.
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    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.
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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.
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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