siliconflow-mcp 0.1.0

High-quality SiliconFlow Image Generation MCP Server

SiliconFlow MCP Server

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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).
• A SiliconFlow API Key. Get one at SiliconFlow Dashboard.

2. Configuration

Create a .env file in the project root (you can copy from .env.example):

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

3. Usage with MCP Clients

This server can be used with any MCP-compatible client.

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": "uv",
      "args": [
        "--directory",
        "C:/path/to/siliconflow-mcp",
        "run",
        "siliconflow_mcp"
      ]
    }
  }
}

Claude Code

Run the following command to add the server:

claude mcp add siliconflow -- uv --directory C:/path/to/siliconflow-mcp run siliconflow_mcp

Gemini CLI

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

{
  "mcpServers": {
    "siliconflow": {
      "command": "uv",
      "args": [
        "--directory",
        "C:/path/to/siliconflow-mcp",
        "run",
        "siliconflow_mcp"
      ]
    }
  }
}

GPT Codex

Configure the MCP server in your GPT Codex settings following the standard MCP server format:

• Name: siliconflow
• Command: uv
• Args: ["--directory", "C:/path/to/siliconflow-mcp", "run", "siliconflow_mcp"]

Note: Always replace C:/path/to/siliconflow-mcp with the actual absolute path to this directory.

Installation for Developers

# 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