io.github.AceDataCloud/mcp-seedream-pro (MCP Server)

MCP server for ByteDance Seedream AI image generation. It is published as mcp-seedream-pro and is distributed via PyPI, with a Python 3.10+ requirement and MIT license. The project is categorized with topics including AI image generation and Model Context Protocol tooling.

🛠️ Key Features

MCP server for ByteDance Seedream AI image generation
Implements model-context-protocol (MCP-compatible)
Package: mcp-seedream-pro (PyPI)

🚀 Use Cases

Integrating Seedream image generation into MCP-based developer workflows
Building developer tools around AI image generation

⚡ Developer Benefits

Uses Python 3.10+
MIT-licensed for reuse in development

⚠️ Limitations

No additional capabilities, tool list, or API details are provided in the available source excerpt.

SeedreamMCP

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, including transparent-background Pro edits
Multiple Models — Seedream v5.0 (flagship), v4.5, and v4.0
Layer Decomposition — Split one image into a base plus up to 16 editable transparent PNG layers
Multi-Resolution — Pro 1K/1.5K/2K; Lite 2K/3K/4K; custom dimensions
Sequential Generation — Generate related images in sequence (5.0 Lite/4.5/4.0)
Web Search — Let 5.0 Lite use current web information when needed
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 images, including Seedream 5.0 Pro transparent-background mode.
`seedream_decompose_image`	Split one image into a base and up to 16 positioned transparent layers.
`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.

Seedream 5.0 capability matrix

Capability	5.0 Pro	5.0 Lite
Single image generation/editing	Yes	Yes
Layer decomposition / transparent background	Yes	No
Sequential images / web search	No	Yes
Prompt optimization	standard, fast	standard
Preset sizes	1K, 1.5K, 2K	2K, 3K, 4K

MCP image tools submit asynchronously and return a task id. Use seedream_get_task until completion. For real-time NDJSON streaming, call the REST API or CLI rather than combining stream with MCP async submission.

Quick Start

1. Get Your API Token

Sign up at AceDataCloud Platform
Go to the API documentation page
Click "Acquire" to get your API token
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:

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

Claude Desktop

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

json

{
  "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):

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):

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 registers the hosted MCP servers with one-click setup.

JetBrains IDEs

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

json

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

Claude Code

Claude Code supports MCP servers natively:

bash

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:

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):

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:

json

{
  "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:

json

{
  "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:

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):

json

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

cURL Test

bash

# 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:

bash

# 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)

json

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

Docker (Self-Hosting)

bash

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-pro-260628`	v5.0 Pro	Generate/Edit	Single image, transparent background, layer decomposition	Tiered Credits
`doubao-seedream-5-0-lite-260128`	v5.0 Lite	Text-to-Image	Sequential generation, streaming, web search	See live pricing
`doubao-seedream-4-5-251128`	v4.5	Text-to-Image	Previous flagship, great quality	See live pricing
`doubao-seedream-4-0-250828`	v4.0	Text-to-Image	Best value, most tasks	See live pricing

Usage Examples

Generate Image from Prompt

code

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

code

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

code

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]

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

bash

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

bash

# 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

bash

# Run unit tests
pytest

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

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

Code Quality

bash

# Format code
ruff format .

# Lint code
ruff check .

# Type check
mypy core tools main.py

Build & Publish

bash

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

# Build package
python -m build

# Upload to PyPI
twine upload dist/*

Project Structure

code

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

Documentation

License

MIT License - see the LICENSE file for details.

io.github.AceDataCloud/mcp-seedream-pro (MCP Server)

🛠️ Key Features

🚀 Use Cases

⚡ Developer Benefits

⚠️ Limitations

Topics

SeedreamMCP

Features

Tool Reference

Seedream 5.0 capability matrix

Quick Start

1. Get Your API Token

2. Use the Hosted Server (Recommended)

Claude.ai

Claude Desktop

Cursor / Windsurf

VS Code (Copilot)

JetBrains IDEs

Claude Code

Cline

Amazon Q Developer

Roo Code

Continue.dev

Zed

cURL Test

3. Or Run Locally (Alternative)

Claude Desktop (Local)

Docker (Self-Hosting)

Available Tools

Image Generation & Editing

Task Management

Information

Available Models

Usage Examples

Generate Image from Prompt

Image Editing

Chinese Prompt Support

Configuration

Environment Variables

Command Line Options

Development

Setup Development Environment

Run Tests

Code Quality

Build & Publish

Project Structure

API Reference

Use Cases

Documentation

License

Links

Install

Configuration

Related servers