
Vocametrix Voice Analysis
io.github.pmarmaroli由 GitHub 账号 pmarmaroli 发布v0.1.1更新于 Oct 24, 2026
Clinical voice analysis MCP server — AVQI, DSI, jitter/shimmer, pronunciation assessment, and more.
概览
官方 Vocametrix MCP 服务器,让助手对 WAV 音频进行临床嗓音与语音分析,并生成治疗材料。
- 可以做什么
- 上传或导入 WAV 音频,获得可复用的 blob 引用用于分析。计算嗓音质量与高级声学指标,如 AVQI、DSI、CPP、HNR、jitter/shimmer、共振峰和音域。评估发音、转写语音、合成语音、测量声级、提取 eGeMAPS 特征、检测音素并分类口吃。运行 AI 代理解读指标、生成练习和词表、辅导词汇并充当言语治疗师。生成、轮询、获取并批准 AI 治疗计划,另有批量和完整评估工作流。
- 适用场景
- 适合言语语言治疗师、嗓音研究者、发音教练和开发者,让助手从 WAV 录音计算临床嗓音指标、评估发音或起草治疗计划。已有带额度的 Vocametrix API 账户时最合适。
- 运行要求
- 本地 stdio 包需要 Node.js 和 npx,或使用托管 HTTP 端点。需要 Vocametrix API 密钥,放在 VOCAMETRIX_API_KEY(托管服务器用 x-api-key 请求头)。需要访问 Vocametrix API 的网络。音频须为 WAV,采样率至少 16 kHz。可选 VOCAMETRIX_MCP_LOCAL_FS 和 VOCAMETRIX_MCP_ALLOW_PRIVATE_HOSTS 开关。
安装
在 SourceWeft 中
- 打开 控制台中的 Vocametrix Voice Analysis,将其添加到工作区。
- 为需要使用其工具的对话启用该服务。
Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。
其他 MCP 客户端
参照 仓库 中的启动说明。
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
来源:README.md,提交 2823fb5
工具
0版本历史
1- v0.1.1最新Sep 16, 2026
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