CloneViral MCP Server

The official Model Context Protocol (MCP) server for CloneViral — AI-powered viral video generation.

Setup

1. Generate an API key at www.cloneviral.ai/mcp-skills
2. Add to your Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json):

{
  "mcpServers": {
    "cloneviral": {
      "command": "npx",
      "args": ["-y", "@cloneviral/mcp-server"],
      "env": {
        "CLONEVIRAL_API_KEY": "cv_your_api_key_here",
        "CLONEVIRAL_API_URL": "https://www.cloneviral.ai"
      }
    }
  }
}

3. Restart Claude Desktop

Available Tools

| Tool | Description | |------|-------------| | cloneviral_list_videos | List your recent generated videos | | cloneviral_get_credits | Check credit balance and subscription | | cloneviral_generate_image | Generate AI images (Flux Pro, GPT Image 2, Nano Banana) | | cloneviral_generate_video | Generate AI videos via text-to-video (Sora 2, Seedance 2, Kling 3) | | cloneviral_check_video_status | Poll generation task status by prediction ID | | cloneviral_analyze_video | Analyze a source video to extract style & structure | | cloneviral_build_remix_variants | Build remix variant prompts from a video analysis | | cloneviral_translate_video | Translate and AI-dub a video into another language | | cloneviral_get_characters | List your saved AI characters |

Remix Workflow

To clone and remix a viral video, use these tools in sequence:

1. cloneviral_analyze_video — Pass the TikTok/YouTube URL to analyze its style
2. cloneviral_build_remix_variants — Generate N variant prompts from the analysis
3. cloneviral_generate_video — Generate each variant as a new video
4. cloneviral_check_video_status — Poll until generation is complete

Video Translation Workflow

1. cloneviral_translate_video — Submit source URL + target language → returns a job ID
2. Check job status at GET /api/video-translate/jobs/{jobId}

Development

npm install
npm run dev    # Run with ts-node
npm run build  # Compile to dist/
npm start      # Run compiled server

License

MIT