SynClub MCP Server

★ 2

from 520chatgpt01

Official SynClub server for AI generation, including text-to-speech, voice cloning, video, and image creation.

🔥🔥🔥✓ VerifiedAccount requiredNeeds API keys

#automation #ai-image #ai-video #voice #git

<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

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 file for details.

From

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

Copy & paste — that's it

# 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

Before it works, you'll need: SYNCLUB_MCP_API

Quick Start

1. Install uv (Python Package Manager)

Copy & paste — that's it

# 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

Edit config file: Configuration Example

Open config file: Configuration Example

Step 2: append this config to your own file

Copy & paste — that's it

{
  "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