MiMo TTS MCP Server
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Alternatives to MiMo TTS MCP Server
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Related Servers
- AlicenseNot gradedqualityDmaintenanceMulti-engine text-to-speech for AI coding assistants. Speaks responses aloud from Claude Code, Cursor, or VS Code via a Claude Code plugin, MCP server, or CLI pipe.54 PyPIMIT
- AlicenseAqualityBmaintenanceText to speech in 149 languages: MP3 links from any assistant. Free without an account. 2,253 voices; PRO adds HD voices, WAV, dialogue with a voice per speaker, Script mode timing and transcription.753 npmMIT
- FlicenseNot gradedqualityDmaintenanceProvides 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.7-

leanvox-mcpofficial
AlicenseNot gradedqualityDmaintenanceEnables text-to-speech generation, voice cloning, dialogue creation, and other TTS operations through natural language in MCP-compatible AI assistants.10 npmMIT- AlicenseNot gradedqualityAmaintenanceEnables MCP-compatible clients such as Claude Desktop and Cursor to generate images and videos, synthesize speech, clone voices, and design custom voices from descriptive prompts. It supports stdio, REST, and SSE transport modes with configurable API hosts, keys, and local or URL-based resource output.183 npmMIT

supertone-mcpofficial
AlicenseAqualityFmaintenanceMCP server for the Supertone TTS API. Generate natural speech, browse and preview the voice catalog, predict synthesis cost, and create cloned voices — directly from Claude Desktop, Cursor, or any MCP-compatible client. Supports Korean, English, Japanese, and 20+ other languages, with speed, pitch, and emotion-style control.144MIT
TDQS
Scored across 4 tools
The three synthesis tools are cleanly differentiated by voice source: preset built-in voice (text_to_speech), invented voice from a description (design_voice_to_speech), and replicated voice from an audio sample (clone_voice_to_speech). list_voices is clearly read-only and metadata-focused, so there is no realistic misselection.
All three synthesis tools follow a predictable '<source>_to_speech' pattern, and the read-only tool uses the conventional 'list_<noun>' form. The convention is consistent and self-explanatory across the whole set.
Four tools is well-scoped for a TTS server: three synthesis modes plus one discovery/introspection tool. Each tool earns its place with no filler or redundancy.
The surface covers the key TTS lifecycle modes (preset, design, clone) plus model/voice discovery, which is strong for the domain. Minor gaps exist around managing generated output (e.g. listing or deleting written files), but agents can work around this via the returned file paths.