Vocametrix MCP Server

@vocametrix/mcp-server

Official Model Context Protocol server for the Vocametrix voice analysis API.

Gives any MCP-compatible AI assistant (Claude Desktop, Cursor, Cline, etc.) direct access to clinical voice metrics, pronunciation assessment, speech transcription, and AI-powered therapy planning.

Quick start

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "vocametrix": {
      "command": "npx",
      "args": ["-y", "@vocametrix/mcp-server"],
      "env": {
        "VOCAMETRIX_API_KEY": "your-api-key-here"
      }
    }
  }
}

Get an API key at vocametrix.com/registration. Free trial: 5 minutes of analysis.

Tools

Voice quality (acoustic)

Advanced voice analysis

Ingestion utilities

Speech and pronunciation

Audio measures

AI agents

Therapy planning

Workflow tools

Resources

• vocametrix://docs/api — API quick reference (auth, rate limits, audio requirements, error codes)
• vocametrix://thresholds/{metric} — Clinical reference thresholds for avqi, dsi, cpp, hnr, jitter-shimmer, gne

Prompts

• interpret_voice_assessment — Generate a clinical SLP-style interpretation report from assessment JSON
• compare_pre_post_therapy — Quantified pre/post therapy narrative with metric-by-metric comparison
• generate_session_report — SOAP-format progress note from pronunciation assessment data

Audio requirements

• Format: WAV (16-bit PCM recommended)
• Sustained vowel tasks: 3+ seconds of /a/ phonation
• Connected speech tasks: 5–30 seconds of read passage
• Minimum sampling rate: 16 kHz

How to pass audio to a tool

The audioPath parameter accepts several input types, but which ones are valid depends on how the MCP server is running:

For chat clients that attach audio in the conversation (Claude.ai web/mobile, etc.), the LLM cannot pass an absolute path to a hosted server — it must call vocametrix_upload_audio first with the file content base64-encoded, then pass the returned blobUrl as audioPath to any analysis tool. The MCP descriptions guide the LLM toward this workflow automatically.

For stdio/local deployments where the MCP runs on the user's own machine, set VOCAMETRIX_MCP_LOCAL_FS=1 to allow analysis tools to read absolute local paths directly — convenient for batch processing of files already on disk.

Environment variables

Development

git clone https://github.com/pmarmaroli/vocametrix-mcp.git
cd vocametrix-mcp
npm install
npm run build
npm test            # run unit tests
npm run inspector   # test with MCP Inspector

MCP Registry

Listed in the official MCP Registry under io.github.pmarmaroli/vocametrix-mcp. Available for one-click installation in MCP-compatible clients (Claude Desktop, Cursor, Zed, Windsurf, and more).

Related projects

The Vocametrix ecosystem:

• 📘 Vocametrix API documentation — full reference for the underlying REST API powering this MCP server.
• 📐 OpenAPI 3.1 specification — machine-readable schema for all 48 endpoints.
• 🐍 vocametrix-python — official Python SDK if you want direct API access from Python (pip install vocametrix).
• 🟦 vocametrix-js — official TypeScript / JavaScript SDK used internally by this MCP server (npm install vocametrix).

License

MIT — see LICENSE