# Lara Translate MCP Server (`maurizio.tiberi/lara-translate-mcp-server`) Actor

Official Apify deployment of the Lara Translate MCP server by Translated. Connect AI assistants to Lara for context-aware translation, language detection, translation memories, and glossaries. Learn more: https://laratranslate.com/

- **URL**: https://apify.com/maurizio.tiberi/lara-translate-mcp-server.md
- **Developed by:** [Maurizio Tiberi](https://apify.com/maurizio.tiberi) (community)
- **Categories:** MCP servers, AI, Open source
- **Stats:** 8 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event + usage

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

### Lara Translate MCP Server

A Model Context Protocol (MCP) Server for Lara Translate API, enabling powerful translation capabilities with support for language detection, context-aware translations and translation memories.

**About this MCP Server:** To understand how to connect to and utilize this MCP server, please refer to the official Model Context Protocol documentation at [mcp.apify.com](https://mcp.apify.com).

***

#### 📚 Table of Contents

- [📖 Introduction](#-introduction)
- [🛠 Available Tools](#-available-tools)
- [🚀 Getting Started](#-getting-started)
- [📋 Requirements](#-requirements)
- [🔌 Installation](#-installation)
- [🧩 Installation Engines](#-installation-engines)
- [💻 Popular Clients that supports MCPs](#-popular-clients-that-supports-mcps)
- [🆘 Support](#-support)

***

#### 📖 Introduction

**What is MCP?**

**How Lara Translate MCP Works**

**Why use Lara inside an LLM?**

***

#### 🛠 Available Tools

**Translation Tools**

- `translate` - Translate text between languages

**Translation Memories Tools**

- `list_memories` - List saved translation memories
- `create_memory` - Create a new translation memory
- `update_memory` - Update translation memory name
- `delete_memory` - Delete a translation memory
- `add_translation` - Add a translation unit to memory
- `delete_translation` - Delete a translation unit from memory
- `import_tmx` - Import a TMX file into a memory
- `check_import_status` - Checks the status of a TMX file import

***

#### 🚀 Getting Started

##### 📋 Requirements

- **Lara Translate API Credentials** (refer to the [Official Documentation](https://laratranslate.com/docs))
- An **LLM client that supports Model Context Protocol (MCP)**, such as Claude Desktop, Cursors, or GitHub Copilot
- **NPX or Docker** (depending on your preferred installation method)

##### 🔌 Installation

**Introduction**

The installation process is standardized across all MCP clients. It involves manually adding a configuration object to your client's MCP configuration JSON file. If you're unsure how to configure an MCP with your client, please refer to your MCP client's official documentation. Lara Translate MCP supports multiple installation methods, including NPX and Docker. Below, we'll use NPX as an example.

**Installation & Configuration**

1. **Step 1:** Open your client's MCP configuration JSON file with a text editor, then copy and paste the following snippet:

   ```json
   {
     "mcpServers": {
       "lara-translate": {
         "command": "npx",
         "args": [
           "-y",
           "@translated/lara-mcp@latest"
         ],
         "env": {
           "LARA_ACCESS_KEY_ID": "<YOUR_ACCESS_KEY_ID>",
           "LARA_ACCESS_KEY_SECRET": "<YOUR_ACCESS_KEY_SECRET>"
         }
       }
     }
   }
   ```

2. **Step 2:** Replace `<YOUR_ACCESS_KEY_ID>` and `<YOUR_ACCESS_KEY_SECRET>` with your Lara Translate API credentials (refer to the [Official Documentation](https://laratranslate.com/docs) for details).

3. **Step 3:** **Restart your MCP client.**

**Verify Installation**

After restarting your MCP client, you should see Lara Translate MCP in the list of available MCPs. The method for viewing installed MCPs varies by client. Please consult your MCP client's documentation. To verify that Lara Translate MCP is working correctly, try translating with a simple prompt:

`Translate with Lara "Hello world" to Spanish`

Your MCP client will begin generating a response. If Lara Translate MCP is properly installed and configured, your client will either request approval for the action or display a notification that Lara Translate is being used.

***

#### 🧩 Installation Engines

##### Option 1: Using NPX

##### Option 2: Using Docker

##### Option 3: Building from Source

- **Using Node.js**

  Clone the repository:

  ```bash
  git clone [https://github.com/translated/lara-mcp.git](https://github.com/translated/lara-mcp.git)
  cd lara-mcp
  ```

  Install dependencies and build:

  ```bash
  # Install dependencies
  pnpm install
  # Build
  pnpm run build
  ```

  Add the following to your MCP configuration file:

  ```json
  {
    "mcpServers": {
      "lara-translate": {
        "command": "node",
        "args": ["<FULL_PATH_TO_PROJECT_FOLDER>/dist/index.js"],
        "env": {
          "LARA_ACCESS_KEY_ID": "<YOUR_ACCESS_KEY_ID>",
          "LARA_ACCESS_KEY_SECRET": "<YOUR_ACCESS_KEY_SECRET>"
        }
      }
    }
  }
  ```

  Replace:

  - `<FULL_PATH_TO_PROJECT_FOLDER>` with the absolute path to your project folder
  - `<YOUR_ACCESS_KEY_ID>` and `<YOUR_ACCESS_KEY_SECRET>` with your actual Lara API credentials.

- **Building a Docker Image**

  Clone the repository:

  ```bash
  git clone [https://github.com/translated/lara-mcp.git](https://github.com/translated/lara-mcp.git)
  cd lara-mcp
  ```

  Build the Docker image:

  ```bash
  docker build -t lara-mcp .
  ```

  Add the following to your MCP configuration file:

  ```json
  {
    "mcpServers": {
      "lara-translate": {
        "command": "docker",
        "args": [
          "run",
          "-i",
          "--rm",
          "-e",
          "LARA_ACCESS_KEY_ID",
          "-e",
          "LARA_ACCESS_KEY_SECRET",
          "lara-mcp"
        ],
        "env": {
          "LARA_ACCESS_KEY_ID": "<YOUR_ACCESS_KEY_ID>",
          "LARA_ACCESS_KEY_SECRET": "<YOUR_ACCESS_KEY_SECRET>"
        }
      }
    }
  }
  ```

  Replace `<YOUR_ACCESS_KEY_ID>` and `<YOUR_ACCESS_KEY_SECRET>` with your actual credentials.

***

#### 💻 Popular Clients that supports MCPs

For a complete list of MCP clients and their feature support, visit the [official MCP clients page](https://modelcontextprotocol.com/clients).

| Client             | Description                                       |
| :----------------- | :------------------------------------------------ |
| Claude Desktop     | Desktop application for Claude AI                 |
| Aixplain           | Production-ready AI Agents                        |
| Cursor             | AI-first code editor                              |
| Cline for VS Code  | VS Code extension for AI assistance               |
| GitHub Copilot MCP | VS Code extension for GitHub Copilot MCP integration |
| Windsurf           | AI-powered code editor and development environment |

***

#### 🆘 Support

- For issues with Lara Translate API: Visit [Lara Translate API and Integrations Support](https://translated.com/support)
- For issues with this MCP Server: Open an issue on [GitHub](https://github.com/translated/lara-mcp/issues)

***

### 🚩 Claim this MCP server. Contact info.

All credits to the original authors of <https://github.com/translated/lara-mcp>

Write to <ai@apify.com>

**Original project URL:** <https://github.com/translated/lara-mcp>

# Actor input Schema

## Actor input object example

```json
{}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("maurizio.tiberi/lara-translate-mcp-server").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("maurizio.tiberi/lara-translate-mcp-server").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call maurizio.tiberi/lara-translate-mcp-server --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,maurizio.tiberi/lara-translate-mcp-server"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/z8nJWBJ0asycR7KyN/builds/3eLoZAXfjHO7Hu9LE/openapi.json