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
Visit Server

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

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured