About Lingvanex Text Translator
Lingvanex Text Translator is an MCP server for translating text between language codes through the Lingvanex API. It supports stdio for Claude Desktop and streamable HTTP for testing and other clients.
Key features
- 01Translate text between languages
- 02stdio and streamable HTTP transports
- 03Lingvanex API integration
Use cases
- 01Translate messages into another language
- 02Connect translation to Claude Desktop
- 03Test translation through HTTP
MCP support
Exposes the `translate_text` tool to MCP clients, accepting text and source and target language codes. Supports stdio and streamable HTTP transports.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEMCP Prototype – Translate Server
This project implements an MCP (Model Context Protocol) server for text translation. The server supports two transports:
- stdio – for integration with Claude Desktop
- http (streamable) – for testing and working via HTTP + SSE
⚙️ Requirements
- Node.js >= 18
- Yarn or npm
- Installed Claude Desktop (for stdio integration)
- Lingvanex Translator account for text translation
🔑 Lingvanex Translator Setup
To use the Lingvanex Translator you'll need a Lingvanex account.
-
If you don't have one, sign up for free
-
Go to the Cloud API tab: Cloud API
-
Fill out the Billing Address data
-
Click Continue to payment
- To get a free trial, it is not necessary to add your payment card
-
Your API key will be generated and visible in the Cloud API tab: API key
Now you are ready to start using the translation API. Below is a video tutorial of the overall process (if available on Lingvanex site).
🚀 Installation & Build
# Clone the repository
git clone https://github.com/lingvanex-mt/MCP-Lingvanex-Translate.git
cd mcp-prototype
Install dependencies
yarn install
🔌 Run in stdio mode (Claude Desktop)
stdio mode is used by Claude Desktop to connect to local MCP servers.
Set environment variable:
TRANSPORT=stdio
Start the server:
yarn build
yarn start
Expected output:
MCP stdio transport running
Translate MCP Server ready
🌐 Run in HTTP mode (streamable)
http mode runs a local HTTP server with HTTP transport.
Useful for browser testing or with curl.
Set environment variables:
TRANSPORT=http
HTTP_PORT=3000
Start the server:
yarn build
yarn start
Test the server:
curl http://127.0.0.1:3000/ping
Expected response:
{ "status": "ok", "transport": "http" }
Use MCP Inspector for debugging:
npx @modelcontextprotocol/inspector
In the MCP Inspector UI, select Transport Type - Streamable HTTP; URL - http://localhost:3000/mcp. Click Connect.
🖥️ Integration with Claude Desktop
Claude Desktop discovers local MCP servers via config file:
- Windows:
%APPDATA%\Claude\claude_desktop_config.json - macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Linux:
~/.config/Claude/claude_desktop_config.json
Example config (Windows)
Open (or create) claude_desktop_config.json and add:
{
"mcpServers": {
"translate": {
"command": "node",
"args": [
"C:\\Users\\path\\to\\project\\dist\\index.js"
]
}
}
}
⚠️ Make sure to update the path to your local
dist/index.jsafter build!
✅ How to verify
- Launch Claude Desktop.
- Enter a request like:
"Use the MCP tool
translate_textto translate 'Hello world' into Russian." - If everything is configured correctly, Claude will call your MCP server and return the translation.
📌 Available Tools
translate_text
Translate text from one language into another.
Arguments:
text– the text to translatesourceLang– source language code (e.g."en")targetLang– target language code (e.g."ru")
Example request:
{
"tool": "translate_text",
"args": {
"text": "Good morning",
"sourceLang": "en",
"targetLang": "fr"
}
}
Example response:
{
"content": [
{ "type": "text", "text": "Bonjour" }
]
}
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.