
Vocametrix Voice Analysis
io.github.pmarmaroli由 GitHub 帳號 pmarmaroli 發布v0.1.1更新於 Oct 24, 2026
Clinical voice analysis MCP server — AVQI, DSI, jitter/shimmer, pronunciation assessment, and more.
概覽
官方 Vocametrix MCP 伺服器,讓助理對 WAV 音訊進行臨床嗓音與語音分析,並產生治療素材。
- 可以做什麼
- 上傳或匯入 WAV 音訊,取得可重複使用的 blob 參照供分析使用。計算嗓音品質與進階聲學指標,例如 AVQI、DSI、CPP、HNR、jitter/shimmer、共振峰與音域。評估發音、轉錄語音、合成語音、測量聲壓級、擷取 eGeMAPS 特徵、偵測音素並分類口吃。執行 AI 代理來解讀指標、產生練習與詞表、輔導詞彙並扮演語言治療師。產生、輪詢、取得並核准 AI 治療計畫,另有批次與完整評估工作流程。
- 適用情境
- 適合語言治療師、嗓音研究者、發音教練與開發者,讓助理從 WAV 錄音計算臨床嗓音指標、評估發音或草擬治療計畫。已有具額度的 Vocametrix API 帳戶時最合適。
- 執行需求
- 本機 stdio 套件需要 Node.js 與 npx,或使用託管的 HTTP 端點。需要 Vocametrix API 金鑰,放在 VOCAMETRIX_API_KEY(託管伺服器用 x-api-key 標頭)。需要連線到 Vocametrix API 的網路。音訊須為 WAV,取樣率至少 16 kHz。可選用 VOCAMETRIX_MCP_LOCAL_FS 與 VOCAMETRIX_MCP_ALLOW_PRIVATE_HOSTS 開關。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Vocametrix Voice Analysis,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
@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):
Get an API key at vocametrix.com/registration. MCP analysis uses purchased API credits; the website subscription and trial do not cover API calls.
Claude Code
Hosted server (no local install):
Or run it locally with npx:
Add --scope user right after claude mcp add to make Vocametrix available in all your projects. Then type /mcp in Claude Code to check the connection.
ChatGPT (OAuth, API credits)
The optional /chatgpt/mcp endpoint links a user's API account through OAuth. The user approves access on the platform's consent page; ChatGPT receives revocable tokens, not the API key. Existing /mcp API-key clients and local stdio clients remain supported.
See ChatGPT setup and release checks for the matching platform changes, database migration, configuration, and tests. This integration must be deployed and tested in ChatGPT before public submission.
Tools
Voice quality (acoustic)
Advanced voice analysis
Ingestion utilities
Speech and pronunciation
Audio measures
AI agents
Therapy planning
Not published on the ChatGPT endpoint (/chatgpt/mcp): these tools take a patient identifier and clinical history, which the ChatGPT app guidelines treat as protected health information. They remain available over stdio and /mcp.
Workflow tools
Resources
vocametrix://docs/api— API quick reference (auth, rate limits, audio requirements, error codes)vocametrix://recording-guide— Recording protocols for every tool (sustained vowel, connected speech with language-specific reference sentences, glissando, sustained /s/ and /z/)vocametrix://thresholds/{metric}— Clinical reference thresholds foravqi,dsi,cpp,hnr,jitter-shimmer,gne
Prompts
interpret_voice_assessment— Generate a clinical SLP-style interpretation report from assessment JSONcompare_pre_post_therapy— Quantified pre/post therapy narrative with metric-by-metric comparisongenerate_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
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 49 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
來源:README.md,提交 2823fb5
工具
0版本歷史
1- v0.1.1最新Sep 16, 2026
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