doubao_image_mcp_server 0.1.0

基于豆包API的图像生成MCP服务器

Doubao Image MCP Server

An image generation MCP server based on FastMCP framework and Volcano Engine API, supporting high-quality image generation through Doubao (doubao-seedream-3.0-t2i) model.

Features

• 🎨 High-Quality Image Generation: Based on Doubao seedream-3.0-t2i model, supports 2K resolution
• 🌐 Bilingual Support: Prompts support both Chinese and English descriptions
• 📐 Multiple Resolutions: Supports various resolutions from 512x512 to 2048x2048
• 🎯 Precise Control: Supports seed, guidance scale, watermark and other parameter controls
• 📁 Local Storage: Automatically downloads and saves generated images to specified directory
• 🔧 MCP Protocol: Fully compatible with MCP protocol, can be integrated with MCP-supported AI assistants
• 📊 Detailed Logging: Complete logging and error handling

Requirements

• Python >= 3.13
• Volcano Engine API Key
• Inference Endpoint Model ID

Installation & Configuration

1. Clone Project

cd doubao_image_mcp_server

2. Install Dependencies

Using uv (recommended):

uv sync

Or using pip:

pip install -e .

3. Configure Environment Variables

This project does not use .env files. All configurations are passed through the environment field in the MCP JSON configuration file.

Add the following configuration to your MCP configuration file:

{
  "mcpServers": {
    "doubao_image_mcp_server": {
      "command": "uv",
      "args": [
        "--directory",
        "C:/WorkSpace/mcp_server/doubao_image_mcp_server",
        "run",
        "doubao_mcp_server.py"
      ],
      "environment": {
        "BASE_URL": "https://ark.cn-beijing.volces.com/api/v3",
        "DOUBAO_API_KEY": "your_api_key_here",
        "API_MODEL_ID": "your_model_id_here",
        "IMAGE_SAVE_DIR": "./images"
      }
    }
  }
}

Environment variables explanation:

• BASE_URL: Doubao (Volcano Engine) platform BASE URL, default: https://ark.cn-beijing.volces.com/api/v3
• DOUBAO_API_KEY: Doubao API key (obtained from Volcano Engine console)
• API_MODEL_ID: Inference endpoint model ID
• IMAGE_SAVE_DIR: Image save directory, default: ./images

4. Get API Key and Model ID

1. Visit Volcano Engine Console
2. Create API key
3. Create inference endpoint, select doubao-seedream-3-0-t2i-250415 model
4. Get endpoint ID (format like: ep-20250528154802-c4np4)

Usage

Start Server

python doubao_mcp_server.py

MCP Tool Calls

The server provides the following MCP tools:

doubao_generate_image

Main tool for image generation.

Parameters:

• prompt (required): Image description text, supports Chinese and English
• size (optional): Image resolution, default "1024x1024"
• seed (optional): Random seed, default -1 (auto-generate)
• guidance_scale (optional): Guidance scale, default 8.0
• watermark (optional): Whether to add watermark, default true
• file_prefix (optional): File name prefix, English only

Supported Resolutions:

• 512x512 - 512x512 (1:1 Small Square)
• 768x768 - 768x768 (1:1 Square)
• 1024x1024 - 1024x1024 (1:1 Large Square)
• 864x1152 - 864x1152 (3:4 Portrait)
• 1152x864 - 1152x864 (4:3 Landscape)
• 1280x720 - 1280x720 (16:9 Widescreen)
• 720x1280 - 720x1280 (9:16 Mobile Portrait)
• 832x1248 - 832x1248 (2:3)
• 1248x832 - 1248x832 (3:2)
• 1512x648 - 1512x648 (21:9 Ultra-wide)
• 2048x2048 - 2048x2048 (1:1 Ultra Large Square)

Example Call:

{
  "tool": "doubao_generate_image",
  "arguments": {
    "prompt": "A cute orange cat sitting on a sunny windowsill, watercolor style",
    "size": "1024x1024",
    "guidance_scale": 8.0,
    "watermark": false,
    "file_prefix": "cute_cat"
  }
}

MCP Resources

resolutions

Get a list of all available image resolutions.

MCP Prompt Templates

image_generation_prompt

Provides prompt templates for image generation, including all parameter descriptions and usage examples.

Standalone Testing

Test Image Generation Tool

python doubao_image_gen.py

Note: Set correct API key and model ID in the code before testing.

Project Structure

doubao_mcp_server/
├── doubao_mcp_server.py    # Main MCP server
├── doubao_image_gen.py     # Core image generation tool
├── .env.example            # Environment variable template
├── .env                    # Environment variable configuration (create yourself)
├── .gitignore             # Git ignore file
├── README.md              # Project documentation
├── pyproject.toml         # Project configuration and dependencies
├── uv.lock               # Dependency lock file
└── log/                  # Log file directory (auto-created)
    ├── doubao_mcp_server.log
    └── doubao_image_gen.log

Logging System

The project includes a complete logging system:

• File Logging: Saved in log/ directory
• Console Logging: Output to stderr for debugging
• Log Levels: DEBUG, INFO, WARNING, ERROR

Error Handling

• ✅ Environment variable validation
• ✅ Parameter type and range checking
• ✅ API call error handling
• ✅ Image download retry mechanism
• ✅ File save exception handling

Technical Features

• Asynchronous Processing: Async image generation based on asyncio
• Retry Mechanism: Automatic retry for failed image downloads
• Parameter Validation: Complete input parameter validation
• Modular Design: Core functionality separated from MCP service
• Type Annotations: Complete type hint support

FAQ

Q: How to get API key?

A: Visit Volcano Engine console and create a new API key in API management.

Q: Where to find Model ID?

A: After creating an inference endpoint in Volcano Engine console, you can find the ID in endpoint details.

Q: What image formats are supported?

A: Currently generated images are saved in JPG format.

Q: How to customize image save path?

A: Modify the IMAGE_SAVE_DIR variable in the .env file.

Q: What to do if generation fails?

A: Check log files and confirm that API key, model ID, and network connection are working properly.

License

This project is open source under the MIT License.

Contributing

Welcome to submit Issues and Pull Requests to improve the project