polyglot-gpu 57 languages on your GPU.
Python translation library + MCP server. TranslateGemma via Ollama — zero cloud dependency, zero API keys.
Install
pip install polyglot-gpu
Translate
result = await translate("Hello", "en", "ja")
MCP
python -m pypolyglot
Features
Everything runs locally on your GPU.
57 Languages
TranslateGemma supports 57 languages including CJK, Arabic, Hindi, and all major European languages.
Dual-Use
Use as a pip-installable Python library or as an MCP server for Claude Code, Claude Desktop, and other clients.
Markdown-Aware
Translates prose while preserving code blocks, tables, HTML, URLs, and badges intact.
Smart Cache
Segment-level cache with Levenshtein fuzzy matching — translation memory that speeds up repeat translations.
Auto-Everything
Auto-starts Ollama, auto-pulls TranslateGemma models. Zero manual setup on first run.
GPU-Safe
Semaphore-controlled concurrency prevents VRAM overload. Works on 4 GB to 24 GB GPUs.
Usage
Install
pip install polyglot-gpu Simple translation
from pypolyglot import translate
result = await translate("Hello world", "en", "ja")
print(result.translation) # こんにちは世界 Markdown translation
from pypolyglot import translate_markdown
result = await translate_markdown(md, "en", "fr")
print(result.markdown) MCP server
# Add to Claude Code config:
{
"mcpServers": {
"polyglot-gpu": {
"command": "polyglot-gpu"
}
}
} Models
Choose based on your GPU VRAM.
MCP Tools
translate_text(text, from_lang, to_lang, model?, glossary?)
Translate text between any of 57 supported languages.
translate_md(markdown, from_lang, to_lang, model?)
Translate markdown while preserving code blocks, tables, and HTML.
translate_all_langs(markdown, from_lang?, languages?, model?, concurrency?)
Translate into multiple languages at once (default: 7 languages).
list_languages()
List all 57 supported languages with codes.
check_status()
Check Ollama availability and installed TranslateGemma models.