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  1. MCP Server

Setup & Installation

What It Does

At its core, the MCP Server acts as a bridge between Lara’s Models and the MCP ecosystem. It allows you to offload translation tasks from general-purpose language models to a specialized engine built specifically for translation, ensuring higher quality—especially for non-English content—and more consistent domain handling.

The server supports features such as automatic source language detection, context injection, and custom instructions (if you plan to use instructions please carefully read here) to guide translation behavior. These make it possible to tailor the translation output to the tone, style, or intent of the interaction—whether it’s a legal document, a casual conversation, or an in-app UI.

Setup

Pick your client below — no API keys needed, just log in through your browser.

Claude Desktop

  1. Go to Settings > Connectors
  2. Click Add Custom Connector
  3. Enter the name: Lara
  4. Enter the URL: https://mcp-v2.laratranslate.com/v1
  5. Click Add, then click Connect
  6. Log in with your Lara Translate credentials in the browser

Done — Lara Translate is now available in your conversations.

Grok

To integrate Lara Translate into Grok using the xAI environment that supports the Model Context Protocol (MCP):

  1. Open the Grok settings or access the MCP services dashboard in your xAI account.

  2. Go to the Connectors (or MCP Tools / Integrations) section.

  3. Click Add Custom Connector (or Add MCP server).

  4. Configure the following parameters:

  1. Click Add, then Connect.

  2. Log in with your Lara Translate credentials in the browser window that will open to complete OAuth authentication.

Cursor

Once Lara Translate is listed in the official Cursor plugin marketplace, install it from inside Cursor:

  1. Open the plugin browser and search for Lara Translate.
  2. Click Install.
  3. The first time you use a Lara tool, your browser will open to authenticate.

In the meantime, or for manual installation, see the Client Setup Guide.

Claude Code

Once Lara Translate is listed in the official Claude Code plugin marketplace, install it from inside Claude Code:

/plugin

Search for Lara Translate and install. The first time you use a Lara tool, your browser will open to authenticate.

In the meantime, or for manual installation, see the Client Setup Guide.

📘

Tips

If you receive this error at the first authentication, log out of the Lara website:{"error":"invalid_request","error_description":"refreshToken is required"}

Other Clients

For step-by-step OAuth setup on VS Code (GitHub Copilot), Windsurf, Cline, Continue, and more, see the Client Setup Guide.

If your client isn't listed, the general approach is to add the server URL (https://mcp-v2.laratranslate.com/v1) to your MCP config — the client will handle OAuth authentication automatically.

Verify It Works

After setup, test with a simple prompt:

Translate with Lara "Hello world" to Spanish

Your client should invoke Lara Translate and return the translation.

Translation Tools

The Lara Translate MCP Server exposes a single core tool: translate. This tool handles multilingual translation requests and supports advanced options to improve output quality and control behavior.

translate

Use the translate tool to perform translations between Supported Languages pairs. Each request allows you to pass multiple text blocks, along with optional metadata to refine translation quality and accuracy.

Supported input fields:

  • text (array): A list of text blocks to be processed. Each block must contain:
    • text (string): The content to translate.
    • translatable (boolean): Whether this block should be translated.
    • source (optional string): ISO code of the source language (e.g., "fr-FR"). If omitted, language detection will be used.
    • target (string): ISO code of the target language (e.g., "en-US").
    • context (optional string): Contextual information to guide translation (e.g., domain, tone, situation).
    • instructions (optional string array): One or more translation instructions (e.g., "Use formal tone", "Avoid slang"), If you plan to use instructions please carefully read here.
    • source_hint (optional string): Additional hint to improve language detection (e.g., "This is likely in Catalan").

Response:

The response is an array of translated text blocks. The structure matches the input format, maintaining the original order and translatable values:

[
  {
    "text": "Translated text",
    "translatable": true
  }
]

Translation Workflow

The main tool exposed by the server is translate, which accepts structured input in JSON format. You can send an array of text blocks, specify which ones should be translated, and optionally provide the source language, contextual hints, or specific instructions.

For example, if you're translating the Italian phrase “la terra è rossa” while chatting with a tennis player, you can pass that context into the request. Rather than returning a literal or ambiguous result, the server will understand that “terra” refers to clay and provide the correct translation: “The clay is red.”

This level of nuance is difficult to achieve with general-purpose models and is one of the key benefits of using Lara within MCP-based systems.

Example

Prompt:
Translate with Lara: "la terra è rossa", I'm talking with a tennis player.

Request:

{
  "text": [
    { "text": "la terra è rossa", "translatable": true }
  ],
  "target": "en-US",
  "context": "Conversation with a tennis player"
}

Response

[
  {
    "text": "The clay is red.",
    "translatable": true
  }
]

More

For more advanced usage, local development instructions, and the latest updates, visit the lara-mcp GitHub repository. There you'll find full documentation on building and running the server locally, contributing to the project, and exploring additional configuration options for Claude Desktop and other MCP-compatible environments.