VoxCPM Audio MCP
Related Servers
Alternatives to VoxCPM Audio MCP
No user-submitted related servers found.
Related Servers
- AlicenseAqualityBmaintenanceEnables any MCP-compatible client to perform local voice cloning and text-to-speech using OmniVoice, including voice profile management, voice design, and an optional ASMR post-processing DSP pipeline.6AGPL 3.0
- AlicenseNot gradedqualityAmaintenanceProvides local speech-to-text and text-to-speech through MCP and HTTP, enabling transcription, voice output, and standalone voice workflows without a gateway.MIT
- AlicenseNot gradedqualityDmaintenanceEnables MCP clients to speak by running local voice models using Chatterbox Turbo TTS or Kokoro TTS, with support for voice cloning, paralinguistic tags, and multiple voices.84 npm13MIT
- AlicenseAqualityBmaintenanceEnables MCP clients to synthesize text into speech locally and play it through the machine's audio, with selectable voices and playback speed.236 PyPIApache 2.0

leanvox-mcpofficial
AlicenseNot gradedqualityDmaintenanceEnables text-to-speech generation, voice cloning, dialogue creation, and other TTS operations through natural language in MCP-compatible AI assistants.9 npmMIT- FlicenseNot gradedqualityNot gradedmaintenanceA local voice interface providing high-performance speech recognition and natural text-to-speech with voice cloning capabilities. It enables AI assistants to speak, listen, and engage in character-based voice conversations through integrated MCP tools.-
TDQS
Scored across 5 tools
speak and speak_segments both synthesize speech, and sing_metadata/sing_notes both synthesize singing; however, descriptions distinguish single vs. multi-segment speech and metadata vs. note-level singing input. An agent can generally tell them apart, though the overlapping pairs may cause occasional misselection.
Most names follow a snake_case verb_noun or verb_object pattern (speak_segments, sing_metadata, sing_notes), with speak as a bare verb and health as a noun utility. The convention is consistent enough to be predictable.
Five tools are well-scoped for an audio synthesis server: two speech modes, two singing modes, and a health check. No obvious bloat or thinness.
The surface covers single and segmented speech, metadata-based and note-based singing, plus system health, which is strong for the stated purpose. Minor gaps like voice/model listing or audio management are not fatal and can be worked around.