MCPSeedream

MCPSeedream

ByteDance Seedream AI image generation and editing (style transfer, background change, virtual try-on) with multiple models, multi-resolution up to 4K, and streaming delivery.

Category
访问服务器

README

MCP Seedream

PyPI version PyPI downloads Python 3.10+ License: MIT MCP

A Model Context Protocol (MCP) server for AI image generation and editing using ByteDance's Seedream models through the AceDataCloud API.

Generate and edit AI images directly from Claude, VS Code, or any MCP-compatible client.

Features

  • Text-to-Image Generation — Create high-quality images from text prompts (Chinese & English)
  • Image Editing — Modify existing images with AI (style transfer, background change, virtual try-on)
  • Multiple Models — Seedream v4.5 (flagship), v4.0 (balanced), v3.0 T2I, SeedEdit v3.0 I2I
  • Multi-Resolution — 1K, 2K, 4K, adaptive, and custom dimensions
  • Seed Control — Reproducible results with seed parameter (v3 models)
  • Sequential Generation — Generate related images in sequence (v4.5/v4.0)
  • Streaming — Progressive image delivery (v4.5/v4.0)
  • Task Tracking — Monitor generation progress and retrieve results

Quick Start

1. Get API Token

Get your API token from AceDataCloud Platform:

  1. Sign up or log in
  2. Navigate to Seedream Images API
  3. Click "Acquire" to get your token

2. Install

# Install from PyPI
pip install mcp-seedream-pro

# Or clone and install locally
git clone https://github.com/AceDataCloud/MCPSeedream.git
cd MCPSeedream
pip install -e .

3. Configure

# Copy example environment file
cp .env.example .env

# Edit with your API token
echo "ACEDATACLOUD_API_TOKEN=your_token_here" > .env

4. Run

# Run the server
mcp-seedream-pro

# Or with Python directly
python main.py

Claude Desktop Integration

Add to your Claude Desktop configuration:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "seedream": {
      "command": "mcp-seedream-pro",
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your_api_token_here"
      }
    }
  }
}

Or if using uv:

{
  "mcpServers": {
    "seedream": {
      "command": "uv",
      "args": [
        "run",
        "--directory",
        "/path/to/MCPSeedream",
        "mcp-seedream-pro"
      ],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your_api_token_here"
      }
    }
  }
}

Remote HTTP Mode (Hosted)

AceDataCloud hosts a managed MCP server that you can connect to directly — no local installation required.

Endpoint: https://seedream.mcp.acedata.cloud/mcp

All requests require a Bearer token in the Authorization header. Get your token from AceDataCloud Platform.

Claude Desktop (Remote)

{
  "mcpServers": {
    "seedream": {
      "type": "streamable-http",
      "url": "https://seedream.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer your_api_token_here"
      }
    }
  }
}

Cursor / VS Code

In your MCP client settings, add:

  • Type: streamable-http
  • URL: https://seedream.mcp.acedata.cloud/mcp
  • Headers: Authorization: Bearer your_api_token_here

cURL Test

# Health check (no auth required)
curl https://seedream.mcp.acedata.cloud/health

# MCP initialize (requires Bearer token)
curl -X POST https://seedream.mcp.acedata.cloud/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -H "Authorization: Bearer your_api_token_here" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}'

Self-Hosting with Docker

docker pull ghcr.io/acedatacloud/mcp-seedream-pro:latest
docker run -p 8000:8000 ghcr.io/acedatacloud/mcp-seedream-pro:latest

Clients connect with their own Bearer token — the server extracts the token from each request's Authorization header and uses it for upstream API calls.

Available Tools

Image Generation & Editing

Tool Description
seedream_generate_image Generate an image from a text prompt
seedream_edit_image Edit or modify existing images with AI

Task Management

Tool Description
seedream_get_task Query a single task status and result
seedream_get_tasks_batch Query multiple tasks at once

Information

Tool Description
seedream_list_models List available models with capabilities
seedream_list_sizes List available image size options

Available Models

Model Version Type Best For Price
doubao-seedream-4-5-251128 v4.5 Text-to-Image Best quality, flagship ~$0.037/image
doubao-seedream-4-0-250828 v4.0 Text-to-Image Best value, most tasks ~$0.030/image
doubao-seedream-3-0-t2i-250415 v3.0 Text-to-Image Reproducible results ~$0.038/image
doubao-seededit-3-0-i2i-250628 v3.0 Image-to-Image Image editing ~$0.046/image

Usage Examples

Generate Image from Prompt

User: Create a photorealistic image of a cat in a garden

Claude: I'll generate that image for you.
[Calls seedream_generate_image with detailed prompt]
→ Returns task_id and image URL

Image Editing

User: Change the background of this photo to a beach
[Provides image URL]

Claude: I'll edit that image for you.
[Calls seedream_edit_image with image URL and edit description]

Chinese Prompt Support

User: 生成一幅中国山水画,有远山、流水和古松

Claude: 好的,我来为您生成这幅山水画。
[Calls seedream_generate_image with Chinese prompt]

Reproducible Generation

User: Generate a landscape and make sure I can recreate the exact same image later

Claude: I'll use the v3 model with a fixed seed.
[Calls seedream_generate_image with model=doubao-seedream-3-0-t2i-250415, seed=42]

Configuration

Environment Variables

Variable Description Default
ACEDATACLOUD_API_TOKEN API token from AceDataCloud Required
ACEDATACLOUD_API_BASE_URL API base URL https://api.acedata.cloud
SEEDREAM_REQUEST_TIMEOUT Request timeout in seconds 1800
LOG_LEVEL Logging level INFO

Command Line Options

mcp-seedream-pro --help

Options:
  --version          Show version
  --transport        Transport mode: stdio (default) or http
  --port             Port for HTTP transport (default: 8000)

Development

Setup Development Environment

# Clone repository
git clone https://github.com/AceDataCloud/MCPSeedream.git
cd MCPSeedream

# Create virtual environment
python -m venv .venv
source .venv/bin/activate  # or `.venv\Scripts\activate` on Windows

# Install with dev dependencies
pip install -e ".[dev,test]"

Run Tests

# Run unit tests
pytest

# Run with coverage
pytest --cov=core --cov=tools

# Run integration tests (requires API token)
pytest -m integration

Code Quality

# Format code
ruff format .

# Lint code
ruff check .

# Type check
mypy core tools main.py

Build & Publish

# Install build dependencies
pip install -e ".[release]"

# Build package
python -m build

# Upload to PyPI
twine upload dist/*

Project Structure

MCPSeedream/
├── core/                   # Core modules
│   ├── __init__.py
│   ├── client.py          # HTTP client for Seedream API
│   ├── config.py          # Configuration management
│   ├── exceptions.py      # Custom exceptions
│   ├── server.py          # MCP server initialization
│   ├── types.py           # Type definitions
│   └── utils.py           # Utility functions
├── tools/                  # MCP tool definitions
│   ├── __init__.py
│   ├── image_tools.py     # Image generation/editing tools
│   ├── task_tools.py      # Task query tools
│   └── info_tools.py      # Model & size info tools
├── prompts/                # MCP prompt templates
│   └── __init__.py
├── tests/                  # Test suite
│   ├── conftest.py
│   ├── test_config.py
│   └── test_utils.py
├── deploy/                 # Deployment configs
│   ├── run.sh
│   └── production/
│       ├── deployment.yaml
│       ├── ingress.yaml
│       └── service.yaml
├── .github/                # GitHub Actions workflows
│   ├── dependabot.yml
│   └── workflows/
│       ├── ci.yaml
│       ├── claude.yml
│       ├── deploy.yaml
│       └── publish.yml
├── .env.example           # Environment template
├── .gitignore
├── .ruff.toml             # Ruff linter config
├── CHANGELOG.md
├── Dockerfile             # Docker image for HTTP mode
├── docker-compose.yaml    # Docker Compose config
├── LICENSE
├── main.py                # Entry point
├── pyproject.toml         # Project configuration
└── README.md

API Reference

This server wraps the AceDataCloud Seedream API:

Use Cases

  • AI Art Creation — Generate stunning artwork, illustrations, and digital art
  • Product Photography — Create professional product scene compositions
  • Content Creation — Generate images for blogs, social media, marketing
  • Virtual Try-On — Visualize clothing on different models
  • Style Transfer — Transform photos into different art styles
  • Game Design — Concept art, character design, environment design
  • E-commerce — Product mockups, lifestyle shots, banner images

License

MIT License - see the LICENSE file for details.

Links

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选