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Voxtral TTS MCP Server

by rocnubie

Voxtral TTS MCP Server

Voxtral TTS Online Free Text to Speech & Voice Clone Speech

MCP Badge Node License: MIT Read Only Zero Config MCP

A Model Context Protocol server that exposes the canonical Voxtral TTS knowledge surface — voice and TTS workflows, FAQ, official links — to MCP-compatible AI clients such as Claude Desktop, Cursor, Windsurf, and Continue. Read-only, no API keys, no quota, ~50 ms cold start.

Official website: https://voxtraltts.online

🎙️ About Voxtral TTS

Voxtral TTS is Mistral AI's text-to-speech platform, accessible at voxtraltts.online, that converts written text into realistic, emotionally expressive speech across nine languages. Built on a 3.4-billion-parameter transformer decoder backbone paired with a flow-matching acoustic transformer and a neural audio codec, the system is designed for production environments where voice quality, low latency, and speaker consistency across languages all matter. The service is available as a hosted API at $0.016 per 1,000 characters, and the underlying model weights are also published on Hugging Face for teams that prefer self-hosted deployment. Whether you need a single narrator voice that holds up across French and Arabic, or a real-time voice agent that responds in under 100 milliseconds, Voxtral TTS is built to cover that range.

Related MCP server: leanvox-mcp

Key Features

  • Low-latency inference: The model delivers approximately 70 ms latency with a real-time factor of around 9.7x, making it suitable for interactive voice applications and live agents rather than just batch narration jobs.

  • Zero-shot voice cloning: A 3-to-25-second reference audio clip is enough to adapt the model to a custom speaker identity, with no fine-tuning pipeline required.

  • Cross-lingual speaker consistency: The same cloned voice can be reused across all nine supported languages — English, French, German, Spanish, Dutch, Portuguese, Italian, Hindi, and Arabic — without losing the speaker's characteristic sound.

  • Emotional style control: Outputs can be guided toward distinct expressive styles including neutral, happy, and sarcastic, giving teams control over tone without recording separate voice assets.

  • Built-in voice library: A set of ready-to-use named voices (Margaret, Paul, Marie, Oliver, and others) lets teams get started immediately without providing reference audio.

  • Flexible deployment: The API integrates directly through Mistral Studio and standard REST endpoints; the open-source weights option allows air-gapped or on-premise deployments for compliance-sensitive environments.

Use Cases

  • Customer support automation: Generate voice responses for IVR systems, automated routing menus, and support bots that need to sound consistent across long sessions and multiple languages.

  • Product onboarding and explainer narration: Turn documentation, tooltips, or walkthrough scripts into spoken audio without recording studio sessions, and update the audio as fast as you update the text.

  • Multilingual marketing and localization: Produce regional campaign audio from a single script using the same speaker voice across language variants, keeping brand voice coherent in every market.

  • Real-time voice agents: Power conversational AI agents, virtual assistants, or phone bots where the round-trip from text to audible speech needs to stay well under a second.

  • Regulated-industry workflows: Use the self-hosted model weights to run speech synthesis entirely within a private infrastructure, meeting data residency requirements in financial services, healthcare, or manufacturing contexts.

Who Is It For

Voxtral TTS is aimed at product teams, engineers, and growth operators who are building voice features into applications rather than looking for a one-off audio tool. The API-first design and per-character pricing model suit developers who want to integrate TTS into a larger pipeline — whether that is a customer-facing chatbot, a localization workflow, or an internal voice agent. The zero-shot cloning capability and cross-lingual consistency make it especially useful for teams serving multilingual audiences who cannot afford to maintain separate voice recordings per language. Teams in regulated industries benefit from the open-source weight option, which lets them run inference entirely on their own infrastructure.

Tools

list_voices

Return the canonical voice and TTS configuration exposed on the site. (Voxtral TTS)

Input: no parameters. Returns: text/markdown.

Return the canonical list of official links for Voxtral TTS (website, support, docs when available).

Input: no parameters. Returns: text/markdown.

Resources

  • site://voxtraltts/voices — Supported voices, languages, and TTS modes.

  • site://voxtraltts/faq — Short FAQ generated from public site metadata.

  • site://voxtraltts/links — Canonical URLs to share with users.

Prompts

tell_me_about_voxtraltts

Summarize what the site is, who it's for, and how it works. — Voxtral TTS

read_aloud_demo_voxtraltts

Plan a read-aloud workflow with the site's voices. — Voxtral TTS

Installation

Install via Smithery

npx -y @smithery/cli install voxtraltts-mcp --client claude

(Replace claude with cursor, windsurf, or continue for those clients.)

Install from source

git clone https://github.com/rocnubie/voxtraltts-mcp.git
cd voxtraltts-mcp
pnpm install

Then add to your MCP client config (claude_desktop_config.json for Claude Desktop, mcp.json for Cursor / Windsurf / Continue):

{
  "mcpServers": {
    "voxtraltts-mcp": {
      "command": "node",
      "args": [
        "/absolute/path/to/voxtraltts-mcp/src/index.mjs"
      ]
    }
  }
}

Debug with MCP Inspector

npx @modelcontextprotocol/inspector node src/index.mjs

Development

pnpm install
pnpm start                 # run the server over stdio

License

MIT

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