Getting Started

Prerequisites

• Node.js 18 or newer
• Ollama installed and running
• A GPU with sufficient VRAM for your chosen model (minimum 3.3 GB for the 4B model)

1. Install Ollama

Download from ollama.com and start it:

ollama serve

On Windows, Ollama typically installs to %LOCALAPPDATA%\Programs\Ollama. Polyglot checks this location automatically when attempting to auto-start Ollama.

2. Pull a model

ollama pull translategemma:12b   # 8.1 GB — best quality/speed balance
# or
ollama pull translategemma:4b    # 3.3 GB — faster, lower quality
# or
ollama pull translategemma:27b   # 17 GB  — highest quality

You can skip this step — Polyglot auto-pulls the model on first use. Pull progress is streamed to stderr so you can monitor the download.

3. Add to your MCP client

Claude Code / Claude Desktop — add to claude_desktop_config.json or .mcp.json:

{
  "mcpServers": {
    "polyglot": {
      "command": "npx",
      "args": ["-y", "@mcptoolshop/polyglot-mcp"]
    }
  }
}

From source:

git clone https://github.com/mcp-tool-shop-org/polyglot-mcp.git
cd polyglot-mcp
npm install && npm run build
node dist/index.js

That’s it. Ask Claude to translate something and it will use the translate tool automatically.

Configuring the default model

Set POLYGLOT_MODEL to override the default:

POLYGLOT_MODEL=translategemma:27b npx @mcptoolshop/polyglot-mcp

Configuring concurrency

By default, Polyglot sends one Ollama request at a time to avoid GPU OOM. If you have plenty of VRAM, increase the limit:

POLYGLOT_CONCURRENCY=2 npx @mcptoolshop/polyglot-mcp

Verifying the setup

Ask Claude to run check_status or use the tool directly. It reports whether Ollama is running and which TranslateGemma models are installed, with their sizes.