SeedreamMCP

<!-- mcp-name: io.github.AceDataCloud/mcp-seedream-pro -->

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 v5.0 (flagship), v4.5, v4.0, v3.0 T2I, SeedEdit v3.0 I2I
• Multi-Resolution — 1K, 2K, 3K, 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

Tool Reference

Tool	Description
seedream_generate_image	Generate an AI image from a text prompt using ByteDance's Seedream model.
seedream_edit_image	Edit or modify existing images using ByteDance's Seedream/SeedEdit model.
seedream_get_task	Query the status and result of a Seedream image generation or edit task.
seedream_get_tasks_batch	Query multiple Seedream image tasks at once.
seedream_list_models	List all available Seedream models with their capabilities and pricing.
seedream_list_sizes	List all available image sizes and resolution options for Seedream.

Quick Start

1. Get Your API Token

1. Sign up at AceDataCloud Platform
2. Go to the API documentation page
3. Click "Acquire" to get your API token
4. Copy the token for use below

2. Use the Hosted Server (Recommended)

AceDataCloud hosts a managed MCP server — no local installation required.

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

All requests require a Bearer token. Use the API token from Step 1.

Claude.ai

Connect directly on Claude.ai with OAuth — no API token needed:

1. Go to Claude.ai Settings → Integrations → Add More
2. Enter the server URL: https://seedream.mcp.acedata.cloud/mcp
3. Complete the OAuth login flow
4. Start using the tools in your conversation

Claude Desktop

Add to your config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):

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

Cursor / Windsurf

Add to your MCP config (.cursor/mcp.json or .windsurf/mcp.json):

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

VS Code (Copilot)

Add to your VS Code MCP config (.vscode/mcp.json):

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

Or install the Ace Data Cloud MCP extension for VS Code, which bundles all 11 MCP servers with one-click setup.

JetBrains IDEs

1. Go to Settings → Tools → AI Assistant → Model Context Protocol (MCP)
2. Click Add → HTTP
3. Paste:

{
  "mcpServers": {
    "seedream": {
      "url": "https://seedream.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Claude Code

Claude Code supports MCP servers natively:

claude mcp add seedream --transport http https://seedream.mcp.acedata.cloud/mcp \
  -h "Authorization: Bearer YOUR_API_TOKEN"

Or add to your project's .mcp.json:

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

Cline

Add to Cline's MCP settings (.cline/mcp_settings.json):

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

Amazon Q Developer

Add to your MCP configuration:

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

Roo Code

Add to Roo Code MCP settings:

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

Continue.dev

Add to .continue/config.yaml:

mcpServers:
  - name: seedream
    type: streamable-http
    url: https://seedream.mcp.acedata.cloud/mcp
    headers:
      Authorization: "Bearer YOUR_API_TOKEN"

Zed

Add to Zed's settings (~/.config/zed/settings.json):

{
  "language_models": {
    "mcp_servers": {
      "seedream": {
        "url": "https://seedream.mcp.acedata.cloud/mcp",
        "headers": {
          "Authorization": "Bearer YOUR_API_TOKEN"
        }
      }
    }
  }
}

cURL Test

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

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

3. Or Run Locally (Alternative)

If you prefer to run the server on your own machine:

# Install from PyPI
pip install mcp-seedream-pro
# or
uvx mcp-seedream-pro

# Set your API token
export ACEDATACLOUD_API_TOKEN="your_token_here"

# Run (stdio mode for Claude Desktop / local clients)
mcp-seedream-pro

# Run (HTTP mode for remote access)
mcp-seedream-pro --transport http --port 8000

Claude Desktop (Local)

{
  "mcpServers": {
    "seedream": {
      "command": "uvx",
      "args": ["mcp-seedream-pro"],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your_token_here"
      }
    }
  }
}

Docker (Self-Hosting)

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.

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-5-0-260128	v5.0	Text-to-Image	Best quality, latest flagship, web search	~$0.040/image
doubao-seedream-4-5-251128	v4.5	Text-to-Image	Previous flagship, great quality	~$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
ACEDATACLOUD_OAUTH_CLIENT_ID	OAuth client ID (hosted mode)	—
ACEDATACLOUD_PLATFORM_BASE_URL	Platform base URL	https://platform.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/SeedreamMCP.git
cd SeedreamMCP

# 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

SeedreamMCP/
├── 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:

• Seedream Images API — Image generation and editing
• Seedream Tasks API — Task queries

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

• AceDataCloud Platform
• Seedream API Documentation
• MCP Protocol
• GitHub Repository
• PyPI Package