siliconflow-mcp 0.1.1

High-quality SiliconFlow Image Generation MCP Server

SiliconFlow MCP Server

[English | 한국어]

An MCP (Model Context Protocol) server for SiliconFlow's image generation service. This allows AI models (like Claude) to generate high-quality images directly using various models available on SiliconFlow.

Features

• generate_image tool: Generate images from text prompts.
  • Supports multiple models (FLUX.1-schnell, FLUX.1-dev, FLUX.2-pro, etc.)
  • aspect_ratio support: Choose from 1:1, 16:9, 9:16, etc.
  • Supports negative_prompt for supported models.
  • Customizable seeds for reproducible generations.
• generate_video tool: Generate videos via text prompts (auto-polls until completion).
  • Supports Wan-AI models and customizable aspect ratios.
• submit_video_generation & get_video_status: Low-level tools for manual async video management.
• list_models tool: Dynamically fetch available image and video models.
• get_user_info tool: Check your SiliconFlow account details, including balance (Total, Paid, Free) and profile info.
• Local Saving: Automatically save .png, .jpg, or .mp4 files to your specified directory.

Setup

1. Prerequisites

• uv installed (recommended) or Python 3.10+.
• A SiliconFlow API Key. Get one at SiliconFlow Dashboard.

2. Configuration

The server requires an API key to function. You can provide it via environment variables or a .env file.

SILICONFLOW_API_KEY=your_api_key_here
# Optional: Path to save generated images/videos locally
SILICONFLOW_IMAGE_DIR=C:/path/to/save/assets

Usage

Using with uvx (Recommended)

You don't need to install anything locally. Just run it directly using uvx:

uvx siliconflow-mcp

Installation via PyPI

You can also install it as a global tool:

uv tool install siliconflow-mcp
# or using pip
pip install siliconflow-mcp

Configuration for MCP Clients

Claude Desktop

Add the following to your Claude Desktop configuration file (%APPDATA%\Claude\claude_desktop_config.json on Windows or ~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

{
  "mcpServers": {
    "siliconflow": {
      "command": "uvx",
      "args": ["siliconflow-mcp"],
      "env": {
        "SILICONFLOW_API_KEY": "your_api_key_here",
        "SILICONFLOW_IMAGE_DIR": "C:/path/to/save/assets"
      }
    }
  }
}

Claude Code

Run the following command:

claude mcp add siliconflow -- uvx siliconflow-mcp

Gemini CLI

Add the configuration to your settings.json (usually located in .gemini/settings.json):

{
  "mcpServers": {
    "siliconflow": {
      "command": "uvx",
      "args": ["siliconflow-mcp"],
      "env": {
        "SILICONFLOW_API_KEY": "your_api_key_here",
        "SILICONFLOW_IMAGE_DIR": "C:/path/to/save/assets"
      }
    }
  }
}

Installation for Developers

If you want to contribute or run from source:

# Install dependencies
uv sync

# Run the server locally
uv run siliconflow_mcp

Supported Models

• black-forest-labs/FLUX.1-schnell (Fast and efficient)
• black-forest-labs/FLUX.1-dev (Higher quality)
• black-forest-labs/FLUX.2-pro (Professional grade)
• ...and other image models hosted on SiliconFlow.

License

MIT