Add waxberry-dev/live-translate-mcp to Translation Services

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Lucas Hornung
2026-06-05 21:49:18 +02:00
parent af81dad1de
commit a019720fb9
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@@ -2678,6 +2678,7 @@ Translation tools and services to enable AI assistants to translate content betw
- [mmntm/weblate-mcp](https://github.com/mmntm/weblate-mcp) 📇 ☁️ - Comprehensive Model Context Protocol server for Weblate translation management, enabling AI assistants to perform translation tasks, project management, and content discovery with smart format transformations. - [mmntm/weblate-mcp](https://github.com/mmntm/weblate-mcp) 📇 ☁️ - Comprehensive Model Context Protocol server for Weblate translation management, enabling AI assistants to perform translation tasks, project management, and content discovery with smart format transformations.
- [shuji-bonji/xcomet-mcp-server](https://github.com/shuji-bonji/xcomet-mcp-server) 📇 🏠 - Translation quality evaluation using xCOMET models. Provides quality scoring (0-1), error detection with severity levels (minor/major/critical), and optimized batch processing with 25x speedup. - [shuji-bonji/xcomet-mcp-server](https://github.com/shuji-bonji/xcomet-mcp-server) 📇 🏠 - Translation quality evaluation using xCOMET models. Provides quality scoring (0-1), error detection with severity levels (minor/major/critical), and optimized batch processing with 25x speedup.
- [translated/lara-mcp](https://github.com/translated/lara-mcp) 🎖️ 📇 ☁️ - MCP Server for Lara Translate API, enabling powerful translation capabilities with support for language detection and context-aware translations. - [translated/lara-mcp](https://github.com/translated/lara-mcp) 🎖️ 📇 ☁️ - MCP Server for Lara Translate API, enabling powerful translation capabilities with support for language detection and context-aware translations.
- [waxberry-dev/live-translate-mcp](https://github.com/waxberry-dev/live-translate-mcp) 📇 🏠 🍎 🐧 - Real-time English ↔ Mandarin Chinese speech translation. Transcribes audio locally with Whisper, translates via Claude API, and synthesises speech locally with Piper TTS. Pass a WAV file path and Claude handles the rest.
### 🎙️ <a name="speech-to-text"></a>Speech-to-Text ### 🎙️ <a name="speech-to-text"></a>Speech-to-Text