synclub-mcp 0.7.9
SynClub MCP Server
Requires Python: >=3.11
Keywords: synclub, mcp, text-to-speech, voice-cloning, video-generation

<h1 align="center">SynClub MCP Server</h1>

<p align="center">
  Official SynClub Model Context Protocol (MCP) Server that enables powerful AI generation capabilities including text-to-speech, voice cloning, video generation, image generation, and more. Compatible with MCP clients like <a href="https://www.anthropic.com/claude">Claude Desktop</a>, <a href="https://www.cursor.so">Cursor</a>, <a href="https://codeium.com/windsurf">Windsurf</a>, and others.
</p>

## Features

-  **Text-to-Speech**: Convert text to natural speech with multiple voice options
-  **Voice Cloning**: Clone voices from audio samples
-  **Video Generation**: Generate videos from text prompts or images
-  **Image Generation**: Create images from text descriptions
-  **Image Recognition**: Analyze and understand image content
-  **Background Removal**: Automatically remove backgrounds from images
-  **HD Image Restoration**: Enhance image quality and resolution
-  **AI Search**: Intelligent search with AI-powered results
-  **Japanese TTS**: Specialized Japanese text-to-speech

## Quick Start

### 1. Install uv (Python Package Manager)

```bash
# macOS/Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows (PowerShell)
powershell -c "irm https://astral.sh/uv/install.sh | iex"

# Or via package managers
# brew install uv
# pip install uv
```

### 2. Get Your API Key

Obtain your API key from your account information page on the SynClub server website.

### 3. Configure Your MCP Client

#### Claude Desktop

**Step 1: find your config file**
You can find your config file at:
- **macOS**: `~/Library/Application Support/Claude/claude_desktop_config.json`
- **Windows**: `%APPDATA%\Claude\claude_desktop_config.json`

Or you can find your config file in claude setting:

Click claude setting:
![Configuration Example](https://raw.githubusercontent.com/520chatgpt01/Synclub-mcp-server/refs/heads/main/image/a573ab2ed4900d8b2478b6d5b91f78e0.jpg)

Edit config file:
![Configuration Example](https://raw.githubusercontent.com/520chatgpt01/Synclub-mcp-server/refs/heads/main/image/7e790df2aefa5dee0aeb40735ac12124.jpg)

Open config file:
![Configuration Example](https://raw.githubusercontent.com/520chatgpt01/Synclub-mcp-server/refs/heads/main/image/ccdfa55185c0f5f4d07a6b7fdf93c0d6.jpg)

**Step 2: append this config to your own file**

```json
{
  "mcpServers": {
    "SynClub": {
      "command": "uvx",
      "args": [
          "synclub-mcp"
      ],
      "env": {
          "SYNCLUB_MCP_API": "your api key"
      }
    }
  }
}
```

If you have any problem with the command uvx, try to use the command `which uvx` to find the absolute path of uvx and replace the command in the config file.

**step 3：save and restart your claude application**
- **important：make sure to restart claude that your config file will update and check the connection in claude developer**

##  Available Tools

| Tool Name | Description |
|-----------|-------------|
| `minimax_text_to_audio` | Convert text to speech with customizable voice settings |
| `minimax_generate_video` | Minimax generate videos |
| `minimax_voice_clone` | Clone voices from audio files |
| `minimax_text_to_image` | Generate images from text prompts |
| `kling_generate_text_to_video` | Start generate videos from text descriptions using Kling models|
| `kling_query_ttv_task` | Get the generate result from generate_text_to_video tool|
| `kling_generate_image_to_video` | Start generate videos from images with text prompts using Kling models|
| `kling_query_gttv_task` | Get the generate result from generate_image_to_video tool|
| `openai_image_recognition` | Analyze and recognize image content |
| `openai_edit_image` | Edit images based on a text prompt |
| `remove_bg` | Automatically remove image backgrounds |
| `hd_restore` | Enhance image quality and resolution |
| `openai_generate_image` | Generate images using alternative models |
| `ai_search` | Perform AI-powered search queries |
| `japanese_tts` | Japanese text-to-speech conversion |
| `generate_comic_story` | Generate a comic story based on input story theme |
| `generate_comic_chapters` | Generate comic story chapters based on novel input, character info and chapter number |
| `generate_comic_image_prompts` | Generate image prompts based on comic story chapter and character info |
| `edit_comic_story` | Edit comic story based on edit prompt and input story. |
| `edit_comic_chapters` | Edit comic chapters based on edit prompt and input chapters. |
| `ugc_tti` | Generate a anime character based on a text prompt |
| `anime_pose_align` | Generate a pose align image based on an anime character image |
| `anime_comic_image` | Generate a comic image based on prompt |
| `flux_edit_image` | edit image based on image url and image prompts |
| `google_nano_tti` | generate image based on text prompt using google nano model |
| `google_nano_edit_image` | Edit and modify existing images based on text prompts using Google Nano banana model |
| `google_nano_edit_image_highlight_feature` | Generate specialized images based on text prompts using Google Nano model for 4 specific highlight features |
| `sora_generate_text_to_video_` | Generate video based on text prompt using sora-2 api
| `veo_generate_text_to_video` | Generate video based on text prompt using google veo api
| `sora_generate_text_to_video_` | Generate video based on text prompt using google veo api
| `flux_pro_tti` | Generate image based on text prompt using flux pro model
| `flux_pro_edit_image` | Generate image based on text prompt and image using flux pro model 
| `google_nano_banana_pro_generate_image` | Generate image based on text prompt and image using Google Nano banana pro model



### Environment Variables

- `SYNCLUB_MCP_API`: Your API key (required)

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## From
https://github.com/520chatgpt01/Synclub-mcp-server