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Nativ MCP Server

mcp-name: io.github.Nativ-Technologies/nativ

AI-powered localization for any MCP-compatible tool — Claude Code, Cursor, Windsurf, and more.

Nativ is a localization platform that uses AI to translate content while respecting your brand voice, translation memory, glossaries, and style guides. This MCP server brings Nativ's full localization engine into your AI coding workflow.

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Why use Nativ via MCP?

  • Translate in-context — localize strings, copy, and content directly from your editor without switching to a browser
  • Translation Memory aware — every translation checks your TM first, ensuring consistency across your project
  • Brand voice built-in — your team's tone, formality, and style guides are applied automatically
  • Review and approve — add approved translations to TM from your editor, building quality over time
  • Multi-format — JSON, CSV, Markdown, or freeform text — Nativ handles it all

Quick Start

For a remote Streamable HTTP connection, see Hosted MCP. Hosted calls use your API key in X-API-Key; the stdio setup below uses NATIV_API_KEY in the environment. JSON-only API clients can import the tools schema and call /tools/{tool_name} with HTTPS media URLs.

1. Get a Nativ API Key

Sign up at dashboard.usenativ.com, go to Settings → API Keys, and create a key. It looks like nativ_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx.

2. Install

Add to your MCP configuration:

Claude Code / Claude Desktop (~/.claude/claude_desktop_config.json)

{
  "mcpServers": {
    "nativ": {
      "command": "npx",
      "args": ["-y", "nativ-mcp"],
      "env": {
        "NATIV_API_KEY": "nativ_your_api_key_here"
      }
    }
  }
}

Cursor (.cursor/mcp.json in your project or ~/.cursor/mcp.json globally)

{
  "mcpServers": {
    "nativ": {
      "command": "npx",
      "args": ["-y", "nativ-mcp"],
      "env": {
        "NATIV_API_KEY": "nativ_your_api_key_here"
      }
    }
  }
}

Windsurf

{
  "mcpServers": {
    "nativ": {
      "command": "npx",
      "args": ["-y", "nativ-mcp"],
      "env": {
        "NATIV_API_KEY": "nativ_your_api_key_here"
      }
    }
  }
}

Note: npx auto-downloads the package on first run — no manual install needed. If uv isn't already on your machine, it will be installed automatically on first launch.

Alternative: use uvx directly

If you already have uv installed and prefer to skip the npm wrapper:

{
  "mcpServers": {
    "nativ": {
      "command": "uvx",
      "args": ["nativ-mcp"],
      "env": {
        "NATIV_API_KEY": "nativ_your_api_key_here"
      }
    }
  }
}

macOS tip: If you get spawn uvx ENOENT in Cursor or Claude Desktop, GUI apps don't inherit your shell PATH. Use the full path (e.g. "command": "/Users/you/.local/bin/uvx") or wrap in a login shell: "command": "/bin/sh", "args": ["-lc", "uvx nativ-mcp"].

3. Use it

Ask your AI assistant things like:

  • "Translate 'Welcome back!' to French and German"
  • "Check our translation memory for existing translations of 'Sign up'"
  • "What are our style guides for localization?"
  • "Localize these i18n strings to all configured languages"
  • "Review this German translation against our TM and brand voice"

Tools

Tool Description
translate Translate text using the full localization engine (TM, style guides, brand voice, glossary)
translate_batch Translate multiple texts to a target language in one call
search_translation_memory Fuzzy-search the translation memory for existing translations
add_translation_memory_entry Add an approved translation to TM for future reuse
get_languages List all configured languages with formality and style settings
get_translation_memory_stats Get TM statistics — total entries, sources, and breakdown
get_style_guides List all style guides with their content and status
get_brand_voice Get the brand voice prompt that shapes all translations
extract_image_text Extract on-image text segments (OCR) in reading order
localize_image Replace on-image text with translations in place, keeping layout and graphics intact
check_image_cultural_fit Flag cultural-sensitivity issues in an image across target markets
transcribe_audio Speech-to-text for a local audio or video file (draft; billed on synthesize)
parse_audio_script Parse a script (.txt/.docx/.pdf/.srt) instead of running STT
list_voices List TTS voices for dubbing
preview_voice Save a short TTS preview WAV to disk
get_voice_consent_script Consent copy required for voice cloning
synthesize_audio Generate billed localized TTS (and optional dubbed MP4) and save to disk
register_video Store a source video for later remux
remux_video Mux a WAV onto a registered video
parse_subtitle Parse a local SRT/ITT into timed cues
localize_subtitles Localize subtitles in-memory from SRT/ITT and/or video STT

Resources

URI Description
nativ://languages Configured languages (JSON)
nativ://style-guides All style guides (JSON)
nativ://brand-prompt Brand voice prompt (JSON)
nativ://tm/stats Translation memory statistics (JSON)

Prompts

Prompt Description
localize-content Guided workflow to localize content into target languages
review-translation Review a translation against TM, style guides, and brand voice
batch-localize-strings Batch-localize i18n strings with structured output

Examples

Translate a marketing headline

You: Translate "The future of luxury, delivered" to French and Japanese

AI: [calls translate tool for each language]

Translation (French): "L'avenir du luxe, livré chez vous"
  TM Match: 0% — new translation, no prior TM entries
  Rationale: "Livré chez vous" adds a personal touch absent from the literal
  "livré", aligning with the brand's premium yet approachable voice.

Translation (Japanese): "ラグジュアリーの未来を、あなたの元へ"
  TM Match: 45% partial — similar pattern found in TM from brand_voice source

Check existing translations

You: Do we have translations for "Add to cart" in our TM?

AI: [calls search_translation_memory]

TM Search Results for "Add to cart" (3 matches):
- 95% [strong] "Add to cart" → "Ajouter au panier" (source: approved)
- 95% [strong] "Add to cart" → "In den Warenkorb" (source: brand_voice)
- 72% [partial] "Add items to cart" → "Ajouter des articles" (source: phrase_tm)

Batch localize i18n strings

You: Localize these to French:
  - "Sign up"
  - "Log in"
  - "Forgot password?"
  - "Continue with Google"

AI: [calls translate_batch]

Batch translation to French (4 items):
1. "Sign up" → "S'inscrire" (TM 100%)
2. "Log in" → "Se connecter" (TM 100%)
3. "Forgot password?" → "Mot de passe oublié ?" (TM 92%)
4. "Continue with Google" → "Continuer avec Google" (TM 85%)

Configuration

Environment Variable Required Description
NATIV_API_KEY Yes Your Nativ API key (nativ_xxx...)
NATIV_API_URL No API base URL (defaults to https://api.usenativ.com)

How It Works

This MCP server acts as a bridge between your AI coding assistant and the Nativ API:

┌─────────────────────┐     ┌──────────────┐     ┌─────────────────┐
│  Claude / Cursor /   │────▶│  Nativ MCP   │────▶│   Nativ API     │
│  Windsurf / etc.     │◀────│  Server      │◀────│ (Translation,   │
│                      │     │  (stdio)     │     │  TM, Styles)    │
└─────────────────────┘     └──────────────┘     └─────────────────┘

The MCP server runs locally via stdio. It authenticates with your API key and calls the Nativ REST API on your behalf. Your AI assistant sees Nativ's tools, resources, and prompts as native capabilities.

Development

# Clone the repo
git clone https://github.com/nativ-ai/nativ-mcp.git
cd nativ-mcp

# Set up environment
uv venv
source .venv/bin/activate
uv pip install -e .

# Run the server (for testing)
NATIV_API_KEY=nativ_xxx nativ-mcp

# Run with MCP Inspector
NATIV_API_KEY=nativ_xxx npx @modelcontextprotocol/inspector uv run nativ-mcp

License

MIT — see LICENSE.

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