MCP server for local speech translation (EN ↔ 中文) via Whisper + Claude + Piper
Live MCP server exists for a simple reason — assistants are far more useful when they can act on Live directly instead of describing what you should do. MCP server for local speech translation (EN ↔ 中文) via Whisper + Claude + Piper.
Give Claude the ability to listen, translate, and speak. live-translate-mcp is a Model Context Protocol (MCP) server that adds speech translation as a native tool inside Claude Desktop and Claude Code. Hand it an audio file, and it transcribes, translates, synthesises, and plays the result — entirely on your machine, with Claude handling the translation.
Once Live is connected, these are the calls the assistant has available:
translate_file — Translate a WAV audio file. Pass an absolute path — the server transcribes it, translates the text via Claude, synthesises speech, savestranslate_speech — Translate raw audio passed as a base64-encoded WAV string. Returns the transcription, translation, and synthesised audio as base64 WAV — useful forhealth_check — Verify that all dependencies (Whisper model cache, Piper voice files, espeak-ng) are present and ready before making a translation requestYou will need one environment variable: ANTHROPIC_API_KEY. The server will not start without them, which is usually why the tools fail to appear on a first run. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
Installation goes through your MCP client rather than a global install: point it at live-translate-mcp on npm and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.
Among the AI and media services options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. Live's toolset — translate_file, translate_speech, health_check — is a fair guide to whether it matches your workflow. It is maintained by dev.waxberry; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
| Tool | What it does |
|---|---|
| translate_file | Translate a WAV audio file. Pass an absolute path — the server transcribes it, translates the text via Claude, synthesises speech, saves <name>_translated.wav next to the original, and plays it automatically. |
| translate_speech | Translate raw audio passed as a base64-encoded WAV string. Returns the transcription, translation, and synthesised audio as base64 WAV — useful for programmatic workflows. |
| health_check | Verify that all dependencies (Whisper model cache, Piper voice files, espeak-ng) are present and ready before making a translation request. |
{
"mcpServers": {
"live-translate": {
"command": "npx",
"args": ["-y", "live-translate-mcp"],
"env": {
"ANTHROPIC_API_KEY": "your-api-key-here"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| ANTHROPIC_API_KEY | Credential the server authenticates with. | Yes |
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.