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audio-mcp

Give 3D AI agents a voice and a face from any MCP client — text-to-speech, speech-to-text, audio-to-face lipsync (ARKit blendshapes), and the motion-capture clip library. Read-only over the live three.ws API; free NVIDIA lanes, no key required.

Install / Use

claude mcp add nirholas -- npx -y github:nirholas/audio-mcp

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

83/100

Supported Platforms

Claude Code
Claude Desktop

Our assessment of audio-mcp

audio-mcp scores 83/100 on our quality scale, 618th of 886 AI & Machine Learning skills we index.

Its MCP Server is 10 KB long, well organised into 15 sections with 7 code examples: a thorough specification that gives an agent plenty to work with.

It has 10 GitHub stars, so there is little community track record yet; judge it on its content.

Substance
29/30
Structure
20/20
Description
15/15
Adoption
4/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated yesterday, so audio-mcp is actively maintained.
  • It is released under the Apache-2.0 license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 97/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

audio-mcp compared with similar skills

All 4 of these similar skills score higher than audio-mcp; compare them before choosing.

SkillScoreStarsUpdatedFormat
audio-mcp (this skill)by nirholas83101d agoMCP Server
claude-memby thedotmack100102.3ktodayCLAUDE.md
Agent-Reachby Panniantong100101.0k2d agoCLAUDE.md
Understand-Anythingby Egonex-AI10087.7ktodayCLAUDE.md
headroomby headroomlabs-ai10077.5ktodayCLAUDE.md

Frequently asked questions

How do I install audio-mcp?
Run claude mcp add nirholas -- npx -y github:nirholas/audio-mcp. The install tabs above show the steps for each supported agent.
Which AI agents does audio-mcp work with?
It is written for Claude Code and Claude Desktop, as a MCP Server file. Other agents that read the same format can often use it too.
Is audio-mcp safe to use?
It is Apache-2.0-licensed and scores 97/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is audio-mcp still maintained?
The repository was last updated yesterday, so audio-mcp is actively maintained.
<p align="center"> <a href="https://three.ws"><img src="https://three.ws/three-ws-mcp-icon.svg" alt="three.ws" width="88" height="88"></a> </p> <h1 align="center">@three-ws/audio-mcp</h1> <p align="center"><strong>Give a 3D AI agent a voice and a face — text-to-speech, speech-to-text, audio-to-face lipsync, and the motion-capture clip library, from any MCP client.</strong></p> <p align="center"> <a href="https://www.npmjs.com/package/@three-ws/audio-mcp"><img alt="npm" src="https://img.shields.io/npm/v/@three-ws/audio-mcp?logo=npm&color=cb3837"></a> <img alt="license" src="https://img.shields.io/npm/l/@three-ws/audio-mcp?color=3b82f6"> <img alt="node" src="https://img.shields.io/node/v/@three-ws/audio-mcp?color=339933&logo=node.js"> <a href="https://registry.modelcontextprotocol.io/?q=io.github.nirholas"><img alt="MCP Registry" src="https://img.shields.io/badge/MCP%20Registry-io.github.nirholas-0ea5e9"></a> <a href="https://three.ws"><img alt="three.ws" src="https://img.shields.io/badge/built%20by-three.ws-000"></a> </p>

A Model Context Protocol server that exposes the three.ws voice and animation pipeline over stdio. Make an avatar speak, let users talk back, turn that speech into a per-frame lipsync track, and browse the recorded motion-capture library — everything you need to drive a 3D agent's mouth and movement.

The speech, recognition, and lipsync lanes run on free NVIDIA NIM models (Magpie TTS, Riva ASR, Audio2Face-3D), with OpenAI as the paid TTS backstop — the same provider policy as the three.ws platform. No key required to start; point THREE_WS_BASE at a deployment and go.

Install

npm install @three-ws/audio-mcp

Or run with npx (no install):

npx @three-ws/audio-mcp

Quick start

Claude Code, one line:

claude mcp add audio -- npx -y @three-ws/audio-mcp

Claude Desktop / Cursor (claude_desktop_config.json or mcp.json):

{
	"mcpServers": {
		"audio": {
			"command": "npx",
			"args": ["-y", "@three-ws/audio-mcp"]
		}
	}
}

Inspect the surface with the MCP Inspector:

npx -y @modelcontextprotocol/inspector npx @three-ws/audio-mcp

Tools

| Tool | Type | What it does | | ---------------------- | --------- | ---------------------------------------------------------------------------------------------------------------------------- | | text_to_speech | read-only | Synthesize spoken audio from text; returns a base64 audio data URL plus the real voice/format/mime. Free Magpie, OpenAI backstop. | | speech_to_text | read-only | Transcribe spoken audio (base64 wav/pcm/flac/ogg) with the free NVIDIA Riva recognizer; returns text, confidence, duration. | | audio_to_face | read-only | Turn speech (text you pass, or audio you have) into a per-frame ARKit blendshape lipsync track via Audio2Face-3D. | | motion_capture_clips | read-only | Browse the motion-capture clip library — recorded face/pose/hand/VMC tracks — with kind filter and cursor pagination. | | motion_capture_clip | read-only | Fetch one clip by id including its full per-frame animation track to play back on an avatar. |

All five tools are read-only: they transform input (synthesize/recognize/animate) or read live library data, never mutating platform state. None are idempotent — the audio bytes, transcript, and catalog move between calls.

Input parameters

text_to_speech — text (required, 1–4096 chars), voice (default nova), format (mp3|opus|aac|flac|wav|pcm, default mp3), model (OpenAI backstop only), language (BCP-47, default en-US), speed (0.5–2.0, OpenAI lane only).

speech_to_text — audio (required, base64 or data: URL), format (wav|pcm|flac|ogg, default wav), language (BCP-47, default en-US), sampleRate (Hz, PCM only), words (bool), model (advanced).

audio_to_face — text or audio (one required), format (wav|pcm, audio path), sampleRate (PCM only), voice / language (text path).

motion_capture_clips — kind (face|pose|hand|vmc), include_public (bool, authenticated only), limit (1–100, default 50), cursor.

motion_capture_clip — id (required, clip UUID).

Examples

// text_to_speech
> { "text": "Hello, I'm your three.ws agent.", "voice": "nova" }
{
  "ok": true,
  "voice": "Magpie-Multilingual.EN-US.Aria",
  "model": "magpie-tts-multilingual",
  "format": "wav",
  "mime": "audio/wav",
  "sizeBytes": 274476,
  "audio": "data:audio/wav;base64,UklGR…"
}
// audio_to_face (text path — returns audio + the lipsync track together)
> { "text": "Watch my lips move." }
{
  "ok": true,
  "audio": { "base64": "UklGR…", "contentType": "audio/wav", "format": "wav" },
  "animation": {
    "fps": 30,
    "blendShapeNames": ["jawOpen", "mouthClose", "…"],
    "durationSec": 1.9,
    "frames": [ { "t": 0.0, "w": [0.0, 0.1, /* … */] } ]
  }
}

A face frame is { t, w }: t = seconds from clip start, w = weights in the order of blendShapeNames (ARKit-52 naming). Play the audio and sample the track by the audio element's currentTime.

Notes on payloads

Audio crosses the wire as base64 (TTS returns it, ASR/A2F accept it). Both the synthesis input (text) and the recognition input (audio, ~8 MB cap) are bounded by the platform — keep clips to a spoken utterance rather than long recordings. For lipsync on audio you already have, pass wav/pcm directly; browser-recorded WebM/Opus must be decoded to WAV or PCM first (Riva and Audio2Face do not accept the WebM container).

Requirements

  • Node.js >= 20.
  • Network access to https://three.ws (or your own THREE_WS_BASE).

Environment variables

| Variable | Required | Default | Purpose | | --------------------- | -------- | ------------------ | ------------------------------------------------------------------------------------------------ | | THREE_WS_BASE | no | https://three.ws | Which deployment to talk to. | | THREE_WS_API_KEY | no | — | Bearer token. Raises the metered TTS/ASR/A2F rate limits and unlocks your own private mocap clips. | | THREE_WS_TIMEOUT_MS | no | 60000 | Per-request timeout for the live model calls. |

Links

  • Homepage: https://three.ws
  • Changelog: https://three.ws/changelog
  • Issues: https://github.com/nirholas/three.ws/issues
  • License: Apache-2.0, see LICENSE

<p align="center"> <sub> Part of the <a href="https://three.ws">three.ws</a> SDK suite — 3D AI agents, on-chain identity, and agent payments.<br/> <a href="https://three.ws">Website</a> · <a href="https://three.ws/changelog">Changelog</a> · <a href="https://github.com/nirholas/three.ws">GitHub</a> </sub> </p> <!-- three.ws:growth -->

Support the project

If audio-mcp saves you time, star it on GitHub. Stars are how other developers and AI agents find the repositories worth trusting, and they cost you one click.

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Built for AI agents too

Coding agents and LLM tooling can read this repo directly: AGENTS.md, llms.txt, llms-full.txt. Point an agent at https://github.com/nirholas/audio-mcp and it has the context it needs.

More from the same author

Contributors

Contributors

Star history

Star History Chart

<!-- /three.ws:growth --> <!-- three.ws:ecosystem -->

Part of three.ws

three.ws is a platform for 3D AI agents with Solana wallets: avatars, a skill marketplace, x402 payments and more than seventy MCP servers. @three-ws/audio-mcp is one package from it.

  • Documentation site: https://nirholas.github.io/audio-mcp/
  • npm: https://www.npmjs.com/package/@three-ws/audio-mcp
  • Canonical source: https://github.com/nirholas/three.ws (this repository is a generated mirror of packages/audio-mcp)
  • Agent-readable summary: llms.txt and AGENTS.md
  • Issues and ideas: https://github.com/nirholas/audio-mcp/issues
<!-- /three.ws:ecosystem -->

Related Skills

View on GitHub
GitHub Stars10
CategoryAI
Updated1d ago
Forks0

Languages

JavaScript

Trust signals

97/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

1 info
audio-mcp — MCP Server: Install & Safety Check | SkillAgent