Lingvanex Text Translator MCP Server

@lingvanex-mt

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

lingvanex-mt

提交者

tech-lingvanex

关于 Lingvanex Text Translator MCP Server

暂无概览

#translate#translator#text-translate#machine-translator

Lingvanex Text Translator MCP Server 配置

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该服务器的 README 中没有可解析的 MCP 配置块，请前往代码仓库查看安装说明。

代码仓库

Lingvanex Text Translator MCP Server 工具

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概览

What is Lingvanex Text Translator?

Lingvanex Text Translator is a Model Context Protocol (MCP) server that provides multilingual text translation via the Lingvanex API. It is designed for use with Claude Desktop or any MCP-compatible client, supporting translation between over 100 languages.

How to use Lingvanex Text Translator?

You need a Lingvanex account and API key. Install dependencies, build the project, and start the server. It can run in stdio mode for Claude Desktop integration, or in HTTP mode to expose a local API for browsers, curl, or other HTTP clients.

Key features of Lingvanex Text Translator

Multilingual text translation powered by Lingvanex API
Supports both stdio (Claude Desktop) and HTTP (API access) transports
Easy integration with Claude Desktop
HTTP mode can serve as a lightweight translation API
Provides a simple tool interface (translate_text)

Use cases of Lingvanex Text Translator

Translating user prompts or documents inside Claude Desktop
Using the HTTP server as a local API for custom apps and services
Connecting third-party tools or scripts to translation via HTTP endpoints
Building multilingual assistants with MCP-compatible clients
Learning and experimenting with MCP integration

常见问题

Can Lingvanex Text Translator work without a Lingvanex API key?

No. You need a free Lingvanex account and API key to use the translation feature.

Is Lingvanex Text Translator free to use?

Yes! The server is open-source, and Lingvanex provides a free trial API key.

Which transports are supported?

stdio for Claude Desktop integration and HTTP for API access.

What are the system requirements?

Node.js >= 18 and a Lingvanex API key. Yarn or npm is recommended for installation.

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