Voxtral TTS MCP
io.github.rocnubie由 GitHub 账号 rocnubie 发布v0.1.0更新于 Oct 24, 2026
Explore Voxtral TTS with API notes, setup guidance, use cases, workflow tips, and FAQ answers for
概览
向 MCP 客户端提供关于 Voxtral TTS 的只读参考资料,包括音色、语言、常见问题与官方链接。
- 可以做什么
- 该服务器提供关于 Voxtral TTS 文本转语音服务的一小套静态知识内容。它包含两个工具 list_voices 和 get_official_links,以及音色、常见问题、链接等资源,还有 tell_me_about_voxtraltts、read_aloud_demo_voxtraltts 等提示词。它本身不合成音频,只返回描述音色、语言、TTS 模式和官方网址的文本与 Markdown。
- 适用场景
- 适合让助手在不浏览网页的情况下回答关于 Voxtral TTS 的问题,或把用户引向其官方页面。它不能用来生成语音、克隆音色或调用 TTS 接口。
- 运行要求
- 以 Node.js 进程通过 stdio 在本地运行,可用 Smithery CLI 安装或从源码用 pnpm 安装。未声明需要 API 密钥、账号或环境变量。
安装
在 SourceWeft 中
- 打开 控制台中的 Voxtral TTS MCP,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
README
Voxtral TTS MCP Server
Voxtral TTS Online Free Text to Speech & Voice Clone Speech
[MCP Badge] [Node] [smithery] [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.
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.
get_official_links
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
(Replace claude with cursor, windsurf, or continue for those clients.)
Install from source
Then add to your MCP client config (claude_desktop_config.json for Claude Desktop, mcp.json for Cursor / Windsurf / Continue):
Debug with MCP Inspector
Official Links
- Website: https://voxtraltts.online
- Support: [email protected]
Development
License
MIT
来源:README.md,提交 82d1400
工具
0版本历史
1- v0.1.0最新Sep 16, 2026
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