Lara-Translate-MCP-Server

ercedes-owe/Lara-Translate-MCP-Server

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The Lara Translate MCP Server is designed to handle translation requests with advanced context-aware capabilities, integrating seamlessly with large language models and providing robust translation memory management.

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Lara Translate MCP Server

The Lara Translate MCP Server handles translation requests for Lara Translate services, providing powerful, context-aware translation capabilities with language detection, translation memories, and seamless API integration. Whether you're building multilingual applications or enhancing language processing in your services, this server enables easy interaction with the Lara Translate API.

     

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Introduction

The Lara Translate MCP Server allows users to perform advanced translation tasks through Model Context Protocol (MCP). It integrates seamlessly with large language models (LLMs) for accurate and contextually aware translations, as well as managing translation memories for enhanced consistency across translations.

Key Features

  • Language Detection: Automatically detects the language of input text.
  • Context-Aware Translations: Ensures accurate translations based on the surrounding context.
  • Translation Memories: Save, update, and manage translation memories for more consistent results over time.
  • MCP Support: Fully integrates with any client supporting the Model Context Protocol.
  • Scalability: Handles multiple translation requests simultaneously with powerful backend capabilities.

Available Tools

Translation Tools

  • translate: Translate text between languages using the Lara Translate engine.

Translation Memories Tools

  • list_memories: Lists all saved translation memories.
  • create_memory: Creates a new translation memory for storing translation units.
  • update_memory: Updates the name or metadata of an existing translation memory.
  • delete_memory: Deletes a translation memory.
  • add_translation: Adds a translation unit to a memory.
  • delete_translation: Deletes a translation unit from a memory.
  • import_tmx: Imports a TMX (Translation Memory eXchange) file into a memory.
  • check_import_status: Checks the status of a TMX file import operation.

Getting Started

Requirements

  • Lara Translate API Credentials: You’ll need to register for the Lara Translate API and obtain your API credentials. Refer to the official documentation for more details.
  • MCP Client: An LLM client that supports Model Context Protocol (MCP), such as Claude Desktop, Cursors, or GitHub Copilot.
  • Installation Tools: You can use either NPX or Docker for installation, depending on your preferred method.

Installation

The installation process is simple and follows a standard configuration for all MCP clients:

  1. Obtain your Lara Translate API credentials.
  2. Add the provided configuration to your MCP client's JSON file (as per the MCP client’s documentation).
  3. Install the necessary dependencies via NPX or Docker.

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