# mcp-server_word-translator

> mcp-server_word-translator — mavline-mcp-server-word-translator. Use this tool when you need to translate DOCX documents while preserving their original formatting and content, such as tables, images, and lists. It solves the problem of translating complex documents with multiple elements, supporting large files through batching and streaming. The tool takes in DOCX files and translation requests, and outputs translated documents with preserved formatting, along with translation status tracking.

Canonical page: https://skillsregistry.net/skills/mavline-mcp-server-word-translator  
JSON: https://api.skillsregistry.net/v1/skills/mavline-mcp-server-word-translator

## Description

Enables translating DOCX documents with the Google Cloud Translation API while preserving original formatting, styles, tables, images, and lists through direct XML manipulation. Supports validation, batching, streaming for large files, and translation status tracking.

## Trust

- **Trust score (0–1):** 0.34
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/re3q5acgs5)
- **Repository:** <https://github.com/Mavline/mcp-server_word-translator>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "mavline-mcp-server-word-translator"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/mavline-mcp-server-word-translator` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/mavline-mcp-server-word-translator/pull`

---
SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt