Image generation MCP server based on Doubao API
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# Doubao Image Generation 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. ## 1. 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 ## 2. Requirements - Python >= 3.13 - Volcano Engine API Key - Inference Endpoint Model ID ## 3. Installation & Configuration ### 3.1 Clone Project ```bash git clone git@github.com:suibin521/doubao-image-mcp-server.git cd doubao-image-mcp-server ``` ### 3.2 Installation Methods #### Method 1: Using uvx for Direct Execution (Recommended) ```bash # Install and run directly from PyPI uvx doubao-image-mcp-server ``` #### Method 2: Using uv to Install to Project ```bash # Install to current project uv add doubao_image_mcp_server ``` #### Method 3: Developer Installation ```bash # After cloning the repository, execute in project root directory uv sync # Or using pip pip install -e . ``` #### Method 4: Traditional pip Installation ```bash pip install doubao_image_mcp_server ``` ### 3.3 Configure Environment Variables This project does not use `.env` files. All configurations are passed through the `env` field in the MCP JSON configuration file. #### 3.3.1 Environment Variable Configuration Example ```json "env": { "BASE_URL": "https://ark.cn-beijing.volces.com/api/v3", "DOUBAO_API_KEY": "your-dev-api-key-her…
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