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Devnagri Translation MCP Server

@DevnagriAI

代码仓库

基本信息

分类

其他

传输方式

stdio

作者

DevnagriAI

提交者

Deva From Devnagri

关于 Devnagri Translation MCP Server

A JavaScript-based Model Context Protocol (MCP) server providing translation, language detection, and supported language listing via Devnagri AI APIs, with a focus on Indic languages.

#mcp#translation#indic#language

Devnagri Translation MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "devnagri-translation": {
      "command": "npx",
      "args": [
        "@devnagriai/devnagriai-translate-mcp",
        "API_KEY=\"your_devnagri_api_key\""
      ]
    }
  }
}

Devnagri Translation MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

点击上方按钮,在临时沙箱中运行此服务器并实时获取工具列表。

概览

What is Devnagri Translation MCP Server?

A Model Context Protocol (MCP) server that provides text translation, language detection, and language listing across 35+ languages, with special support for major Indic languages. It is designed for developers integrating AI tools like Cursor, Claude, Windsurf, or other MCP-compatible platforms.

How to use Devnagri Translation MCP Server?

Run it directly via NPX with your API key: npx @devnagriai/devnagriai-translate-mcp API_KEY="your_devnagri_api_key". It can also be set up locally with a .env file and standard MCP CLI tools. Once running, the server exposes three tools: translate, detect_language, and list_supported_languages.

Key features of Devnagri Translation MCP Server

  • Translation between 35+ languages including all major Indic languages.
  • Language detection for any input text.
  • Lists all supported languages on demand.
  • MCP protocol ready for AI tool integration.
  • Robust error handling and validation.
  • Extensive test suite.

Use cases of Devnagri Translation MCP Server

  • Building multilingual AI assistants that translate user queries in real time.
  • Adding language detection to content pipelines or chat applications.
  • Providing users with a list of available languages for selection in translation UIs.

常见问题

1

What runtime or dependencies does the server require?

It runs via NPX (Node.js) or a local Node environment. An API key from Devnagri is required.

2

Where does the translation data live?

Translations are processed through the Devnagri API; no data is stored locally by the server.

3

How do I configure it for Cursor or Claude?

Use the standard MCP configuration: set the command to `npx @devnagriai/devnagriai-translate-mcp` and pass the `API_KEY` environment variable.

4

What transports or authentication does it support?

The server uses standard MCP transport (stdio). Authentication is via the API key passed at startup.

5

Are there any known limits or rate limits?

The README does not specify any; consult the Devnagri API documentation for usage limits.

评论

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