这是一个 Model Context Protocol (MCP) 服务器，通过 AceDataCloud API 使用字节跳动 Seedream 模型进行 AI 图像生成和编辑。
直接从 Claude、VS Code 或任何兼容 MCP 的客户端生成和编辑 AI 图像。
文本生成图像 (Text-to-Image) — 根据文本提示词（中英文）创建高质量图像
图像编辑 (Image Editing) — 使用 AI 修改现有图像（风格迁移、背景更换、虚拟试穿）
多种模型 — Seedream v5.0（旗舰版）、v4.5、v4.0、v3.0 T2I、SeedEdit v3.0 I2I
多分辨率 — 支持 1K、2K、3K、4K、自适应及自定义尺寸
种子控制 (Seed Control) — 通过种子参数实现可复现的结果（v3 模型）
序列生成 — 按顺序生成相关图像（v4.5/v4.0）
流式传输 — 渐进式图像交付（v4.5/v4.0）
任务追踪 — 监控生成进度并获取结果
Related MCP server: Doubao Image/Video Generation MCP Server
工具 | 描述 |
| 使用字节跳动 Seedream 模型根据文本提示词生成 AI 图像。 |
| 使用字节跳动 Seedream/SeedEdit 模型编辑或修改现有图像。 |
| 查询 Seedream 图像生成或编辑任务的状态和结果。 |
| 一次性查询多个 Seedream 图像任务。 |
| 列出所有可用的 Seedream 模型及其功能和定价。 |
| 列出 Seedream 所有可用的图像尺寸和分辨率选项。 |
在 AceDataCloud 平台 注册账号
前往 API 文档页面
点击 “Acquire” 获取您的 API token
复制该 token 以备后用
AceDataCloud 托管了一个 MCP 服务器 —— 无需本地安装。
端点： https://seedream.mcp.acedata.cloud/mcp
所有请求都需要 Bearer token。请使用第 1 步中获取的 API token。
通过 OAuth 直接在 Claude.ai 上连接 —— 无需 API token：
前往 Claude.ai 设置 (Settings) → 集成 (Integrations) → 添加更多 (Add More)
输入服务器 URL: https://seedream.mcp.acedata.cloud/mcp
完成 OAuth 登录流程
开始在对话中使用这些工具
添加到您的配置文件（macOS 上为 ~/Library/Application Support/Claude/claude_desktop_config.json）：
{
"mcpServers": {
"seedream": {
"type": "streamable-http",
"url": "https://seedream.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}添加到您的 MCP 配置文件（.cursor/mcp.json 或 .windsurf/mcp.json）：
{
"mcpServers": {
"seedream": {
"type": "streamable-http",
"url": "https://seedream.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}添加到您的 VS Code MCP 配置文件（.vscode/mcp.json）：
{
"servers": {
"seedream": {
"type": "streamable-http",
"url": "https://seedream.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}或者为 VS Code 安装 Ace Data Cloud MCP 扩展，该扩展捆绑了所有 15 个 MCP 服务器，支持一键设置。
前往 设置 (Settings) → 工具 (Tools) → AI Assistant → Model Context Protocol (MCP)
点击 添加 (Add) → HTTP
粘贴：
{
"mcpServers": {
"seedream": {
"url": "https://seedream.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}Claude Code 原生支持 MCP 服务器：
claude mcp add seedream --transport http https://seedream.mcp.acedata.cloud/mcp \
-h "Authorization: Bearer YOUR_API_TOKEN"或者添加到您项目的 .mcp.json 中：
{
"mcpServers": {
"seedream": {
"type": "streamable-http",
"url": "https://seedream.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}添加到 Cline 的 MCP 设置 (.cline/mcp_settings.json)：
{
"mcpServers": {
"seedream": {
"type": "streamable-http",
"url": "https://seedream.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}添加到您的 MCP 配置中：
{
"mcpServers": {
"seedream": {
"type": "streamable-http",
"url": "https://seedream.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}添加到 Roo Code 的 MCP 设置中：
{
"mcpServers": {
"seedream": {
"type": "streamable-http",
"url": "https://seedream.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}添加到 .continue/config.yaml：
mcpServers:
- name: seedream
type: streamable-http
url: https://seedream.mcp.acedata.cloud/mcp
headers:
Authorization: "Bearer YOUR_API_TOKEN"添加到 Zed 的设置 (~/.config/zed/settings.json)：
{
"language_models": {
"mcp_servers": {
"seedream": {
"url": "https://seedream.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
}# 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"}}}'如果您更喜欢在自己的机器上运行服务器：
# 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{
"mcpServers": {
"seedream": {
"command": "uvx",
"args": ["mcp-seedream-pro"],
"env": {
"ACEDATACLOUD_API_TOKEN": "your_token_here"
}
}
}
}docker pull ghcr.io/acedatacloud/mcp-seedream-pro:latest
docker run -p 8000:8000 ghcr.io/acedatacloud/mcp-seedream-pro:latest客户端使用各自的 Bearer token 进行连接 —— 服务器会从每个请求的 Authorization 标头中提取 token。
工具 | 描述 |
| 根据文本提示词生成图像 |
| 使用 AI 编辑或修改现有图像 |
工具 | 描述 |
| 查询单个任务的状态和结果 |
| 一次性查询多个任务 |
工具 | 描述 |
| 列出可用模型及其功能 |
| 列出可用的图像尺寸选项 |
模型 | 版本 | 类型 | 最佳用途 | 价格 |
| v5.0 | 文本生成图像 | 最佳质量，最新旗舰，支持网页搜索 | ~$0.040/张 |
| v4.5 | 文本生成图像 | 前旗舰版，质量优异 | ~$0.037/张 |
| v4.0 | 文本生成图像 | 性价比最高，任务处理量大 | ~$0.030/张 |
| v3.0 | 文本生成图像 | 可复现结果 | ~$0.038/张 |
| v3.0 | 图像生成图像 | 图像编辑 | ~$0.046/张 |
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 URLUser: 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]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]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]变量 | 描述 | 默认值 |
| 来自 AceDataCloud 的 API token | 必需 |
| API 基础 URL |
|
| OAuth 客户端 ID（托管模式） | — |
| 平台基础 URL |
|
| 请求超时时间（秒） |
|
| 日志级别 |
|
mcp-seedream-pro --help
Options:
--version Show version
--transport Transport mode: stdio (default) or http
--port Port for HTTP transport (default: 8000)# 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 unit tests
pytest
# Run with coverage
pytest --cov=core --cov=tools
# Run integration tests (requires API token)
pytest -m integration# Format code
ruff format .
# Lint code
ruff check .
# Type check
mypy core tools main.py# Install build dependencies
pip install -e ".[release]"
# Build package
python -m build
# Upload to PyPI
twine upload dist/*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此服务器封装了 AceDataCloud Seedream API：
Seedream Images API — 图像生成与编辑
Seedream Tasks API — 任务查询
AI 艺术创作 — 生成精美的艺术品、插画和数字艺术
产品摄影 — 创建专业的产品场景构图
内容创作 — 为博客、社交媒体、营销生成图像
虚拟试穿 — 在不同模特身上可视化服装效果
风格迁移 — 将照片转换为不同的艺术风格
游戏设计 — 概念艺术、角色设计、环境设计
电子商务 — 产品样机、生活方式照片、横幅图像
Decompose one image into a base image and up to 16 editable transparent layers.
| Name | Required | Description | Default |
|---|---|---|---|
| size | No | Output size: auto, 1K, 1.5K, or 2K. | auto |
| image | Yes | One PNG or JPEG URL/base64 image to decompose. | |
| prompt | No | Optional elements to decompose; omit for automatic decomposition. Supports <bbox> coordinates. | |
| watermark | No | Whether to add an AI-generated watermark. | |
| callback_url | No | Optional webhook URL for async delivery. | |
| output_format | No | Base image format; layers are always PNG. | jpeg |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It usefully discloses the output structure (base image plus up to 16 transparent layers), but it does not disclose side effects or caveats such as async task behavior, default watermarking, non-destructiveness, or cost/rate implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence contains a verb, object, and output shape with no filler. The key information is front-loaded, and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a six-parameter tool with an output schema and no annotations, the description is serviceable but incomplete: it omits the asynchronous/deferred result path implied by callback_url and the need to poll via seedream_get_task, and it does not address watermark or task lifecycle behavior. However, the input schema is thorough and the output schema is present, closing some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents all six parameters and the enum. The top-level description adds no parameter-level meaning beyond the schema, which matches the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Decompose') with a clear resource and outcome: one input image becomes a base image plus up to 16 editable transparent layers. This distinguishes it from sibling tools like seedream_edit_image or seedream_generate_image even without explicitly naming them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The intended use is implied by the verb and the layer output, but the description does not explicitly state when an agent should choose decompose over edit_image, nor does it mention exclusions or prerequisites. Sibling tool names provide some context, but the description itself gives no direct routing guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Edit or modify existing images using ByteDance's Seedream/SeedEdit model.
This tool modifies existing images based on text instructions. It can change
styles, backgrounds, attributes, clothing, and more. Supports single or
multiple image inputs.
Use this when:
- You want to modify or transform an existing image
- You need to change style, background, colors, or attributes
- You want to apply artistic transformations (watercolor, oil painting, etc.)
- You need virtual try-on (clothing on person)
- You want to place objects in different scenes
Common use cases:
- Style transfer: "Convert to anime style", "Make it look like a pencil sketch"
- Background change: "Replace background with a sunset beach"
- Attribute edit: "Change hair color to blonde", "Add sunglasses"
- Virtual try-on: Provide person image + clothing image
- Scene composition: Place products in realistic environments
Returns:
JSON with task_id, trace_id, success status, and edited image data
including image URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| size | No | Model-specific output size or explicit dimensions. Pro supports 1K/1.5K/2K; Lite supports 2K/3K/4K. | |
| image | Yes | List of image URLs or base64-encoded images to edit. Supports HTTP/HTTPS URLs (publicly accessible) or base64 format (data:image/png;base64,...). Each image must be under 10MB. | |
| model | No | Model to use for editing. Seedream 5.0 Pro, 5.0 Lite, 4.5, and 4.0 all support image editing when images are provided. | doubao-seedream-5-0-lite-260128 |
| tools | No | Optional list of tool types for the model to use during editing. | |
| prompt | Yes | Description of the edit to perform on the image(s). Describe what changes you want. Example: 'Change the background to a beach scene', 'Make the person wear a red dress', 'Convert to watercolor painting style' | |
| watermark | No | Whether to add an AI-generated watermark. Default is true. | |
| background | No | Seedream 5.0 Pro background mode. transparent requires one PNG input and PNG output. | |
| callback_url | No | Optional webhook URL for async result notification. | |
| output_format | No | Output image format. 'jpeg' (default) or 'png'. | |
| response_format | No | Response format. 'url' (default) or 'b64_json'. | |
| optimize_prompt_options | No | Prompt optimization. Pro supports standard/fast; Lite supports standard. | |
| sequential_image_generation | No | Generate related images based on input. 'auto' enables it. | |
| sequential_image_generation_options | No | Tunable options for grouped image generation. |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden, and it does disclose the return payload (task_id, trace_id, success, image URLs), watermark defaulting to true, and the PNG constraint for transparent background. However it never says whether the call is synchronous or asynchronous (the mere existence of callback_url implies async), nor mentions permissions, cost, latency, or failure modes for a 13-parameter generation job.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Purpose and scope are front-loaded, which is good, but the 'Use this when' bullets and the 'Common use cases' bullets substantially restate the same ground (style, background, attributes, virtual try-on), so several sentences do not fully earn their place. Structure is readable but repetitive.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 13 parameters, an output schema already present, and 100% schema coverage, the description supplies what structured fields cannot: the intent-level taxonomy of edits and multi-image input semantics. The main remaining gap is async/execution behavior, but for a tool of this complexity the description is largely complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents size, model, background, output_format and the rest; the description only adds illustrative prompt examples ('Make the person wear a red dress'). Per the coverage rule this is a baseline 3, and the description does not add much beyond the schema for the remaining parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('Edit or modify existing images') and immediately scopes it to image-to-image transformation driven by text instructions. The framing as modification of an existing image implicitly but clearly separates it from the sibling seedream_generate_image, and an agent can tell which one to pick without opening a schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
A dedicated 'Use this when' block plus five concrete use-case bullets give strong positive guidance (style transfer, background change, attribute edit, virtual try-on, scene composition). It never names an alternative tool or states a when-not condition (e.g. use generate_image when no source image exists), so it stops short of 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Generate an AI image from a text prompt using ByteDance's Seedream model.
This tool creates high-quality images from text descriptions using ByteDance's
Seedream models (powered by Doubao). Supports multiple model versions with different
capabilities and quality levels.
Use this when:
- You want to generate a new image from scratch based on a text description
- You need high-quality AI-generated images (photos, illustrations, art)
- You want to create images with specific styles, compositions, or themes
Do NOT use this when:
- You want to edit or modify an existing image (use seedream_edit_image instead)
- You need to combine multiple images (use seedream_edit_image instead)
Model selection guide:
- v5.0 Lite (doubao-seedream-5-0-lite-260128): Image sets, streaming, and web search
- v4.5 (doubao-seedream-4-5-251128): Previous flagship, great quality and detail
- v4.0 (doubao-seedream-4-0-250828): Stable and cost-effective, great for most tasks
Returns:
JSON with task_id, trace_id, success status, and generated image data
including image URLs.
| Name | Required | Description | Default |
|---|---|---|---|
| size | No | Model-specific output size: Pro supports 1K/1.5K/2K (and auto for decomposition); Lite supports 2K/3K/4K. Explicit dimensions such as 2048x1024 are also accepted. | |
| model | No | Model to use for generation. 'doubao-seedream-5-0-pro-260628' (v5.0 Pro, flagship single image, highest quality; no sequential generation, streaming, or web search). 'doubao-seedream-5-0-lite-260128' (v5.0 Lite, sequential generation, streaming, web search). 'doubao-seedream-4-5-251128' (v4.5, previous flagship, great quality). 'doubao-seedream-4-0-250828' (v4.0, stable, best value). | doubao-seedream-5-0-lite-260128 |
| tools | No | Optional list of tool types for the model to use during generation. Currently only 'web_search' is supported. Only supported by doubao-seedream-5-0-lite-260128 (v5.0 Lite). | |
| prompt | Yes | Description of the image to generate. Be descriptive about subject, style, atmosphere, lighting, and composition. Supports both Chinese and English. Example: 'A photorealistic portrait of an astronaut on Mars, golden hour lighting, cinematic composition, ultra-detailed' | |
| watermark | No | Whether to add an AI-generated watermark. Default is true. | |
| callback_url | No | Optional webhook URL to receive the result asynchronously. The API will POST the result to this URL when complete. Must be publicly accessible. | |
| output_format | No | Output image format. 'jpeg' (default) or 'png'. | |
| response_format | No | Response format for the generated image. 'url' (default) returns a public image URL. 'b64_json' returns base64-encoded image data. | |
| optimize_prompt_options | No | Optional prompt optimization configuration. Supports `mode` with values 'standard' (higher quality, slower) or 'fast' (quicker, lower quality). Only supported on doubao-seedream-4.5 (standard mode only) and doubao-seedream-4.0. | |
| sequential_image_generation | No | Generate related images based on input. 'auto' enables it, 'disabled' (default) turns it off. Supported by Seedream 5.0 Lite, 4.5, and 4.0; not Pro. | |
| sequential_image_generation_options | No | Tunable options for grouped image generation. Only honored when `sequential_image_generation=auto`. Supports `max_images` (int, range [1, 15]). Supported by Seedream 5.0 Lite, 4.5, and 4.0; not Pro. |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden, and it does disclose the async task model (task_id/trace_id, callback_url), the model capability differences (streaming, sequential generation, web search only on Lite/4.5/4.0, not Pro), and the return payload shape. It stops short of stating auth requirements, rate limits, or generation latency, so a small gap remains.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loaded with the core action, then organized into scannable when/when-not/model blocks and a Returns section. It is slightly long and the model guide duplicates schema enum text, but nothing is unearned.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an 11-parameter generation tool with a full output schema, the description covers the generation intent, model trade-offs, and async return shape adequately. It omits practical operational context such as authentication, billing, or typical generation time, which an agent may still need.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The model selection guide partially restates schema enum descriptions (e.g. Lite supports streaming/web search) rather than adding net-new semantics, though it helps consolidate capability trade-offs in one place.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (generate) and resource (AI image) plus the underlying model family, and explicitly distinguishes itself from seedream_edit_image for the editing/combining cases. An agent can identify this as the text-to-image entry point without opening another schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit 'Use this when' and 'Do NOT use this when' blocks, naming seedream_edit_image as the alternative for modification and multi-image combination. The model selection guide further routes among capability tiers.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Query the status and result of a Seedream image generation or edit task.
Use this to check if a generation/edit is complete and retrieve the resulting
image URLs and metadata.
Use this when:
- You want to check if an image generation has completed
- You need to retrieve image URLs from a previous generation
- You want to get the full details of a generated/edited image
Returns:
Task status and image information including URLs, prompts, and metadata.
| Name | Required | Description | Default |
|---|---|---|---|
| task_id | Yes | The task ID returned from a generation or edit request. This is the 'task_id' field from any seedream_generate_image or seedream_edit_image tool response. |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses it returns status and image information, implying a read-only operation. With no annotations, the description carries the burden and does well, though it could explicitly state it is non-destructive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Concisely structured with bulleted usage scenarios and a return summary, though some minor repetition between the first line and the list.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present and a single required parameter, the description fully covers the tool's purpose and usage, leaving no gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description's parameter info duplicates the schema description, adding no new meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it queries the status and result of a specific task, distinguishing it from sibling tools like seedream_generate_image and seedream_get_tasks_batch.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit use cases (checking completion, retrieving URLs, getting full details) but does not mention when not to use or compare to seedream_get_tasks_batch.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Query multiple Seedream image tasks at once.
Efficiently check the status of multiple tasks in a single request.
More efficient than calling seedream_get_task multiple times.
Use this when:
- You have multiple pending generations to check
- You want to get status of several images at once
- You're tracking a batch of generations
Returns:
Status and image information for all queried tasks.
| Name | Required | Description | Default |
|---|---|---|---|
| task_ids | Yes | List of task IDs to query. Allows querying multiple tasks at once. |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It describes the operation as querying (read-only) and states it returns 'Status and image information'. It does not mention auth requirements or rate limits, but for a query tool, this is sufficient. Slightly more detail on the response format would improve, but overall transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with a clear initial sentence, a bullet-style list for usage scenarios, and a returns section. No redundant information; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (1 parameter, no annotations, output schema exists), the description sufficiently covers purpose, usage, and returns. It doesn't explain output schema details, but that's acceptable as the schema itself is present. A hint about pagination or result format could improve, but not necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear parameter description. The tool description adds context about efficiency and use cases but does not add new parameter semantics beyond what the schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Query multiple Seedream image tasks at once' and distinguishes from the sibling tool 'seedream_get_task' by highlighting batch efficiency. The verb 'query' and resource 'tasks' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use scenarios: 'when you have multiple pending generations', 'when you want to get status of several images at once', 'when tracking a batch'. Although not explicitly stating when not to use, it implies the alternative for single tasks (seedream_get_task).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all available Seedream models with their capabilities and pricing.
Use this when:
- User asks what models are available
- You need to help choose the right model for a task
- You want to compare model capabilities
Returns:
Formatted table of all Seedream models with descriptions.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states it returns a formatted table with descriptions, implying no side effects. Does not mention authentication requirements or data freshness, but for a read-only listing tool it is adequately transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Concise: one line for purpose, bulleted use cases, and output format. No fluff. Well-structured and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and an output schema exists, description is complete. Explains what models are listed and for what purpose. Does not need to explain return values since output schema covers that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters in input schema. Description compensates by detailing what the output includes (capabilities, pricing, descriptions). Baseline 4 for zero-param tools where description adds meaningful output context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it lists all available Seedream models with capabilities and pricing. Specific verb 'list' and resource 'models'. Distinguishes from sibling tools which focus on editing, generating, or retrieving tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly lists three use cases: user asks about models, need to choose a model, want to compare capabilities. Does not mention when not to use, but that is not critical for a simple listing tool. No alternative tools suggested, but sibling tools are distinct in purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List all available image sizes and resolution options for Seedream.
Use this when:
- User asks about available image sizes
- You need to help choose the right resolution
- You want to understand size options
Returns:
Formatted list of all size options with descriptions.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states it returns a 'formatted list of all size options with descriptions', which is sufficient for a simple read-only listing tool with no parameters. It does not disclose potential rate limits or side effects, but these are minimal for such a tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with a clear 'Use this when' section and a 'Returns' section. Every sentence adds value, and the structure is front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has zero parameters and a simple list output, the description fully covers its purpose, usage context, and return value. The output schema exists, and the description notes the return format adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, and schema description coverage is 100%. Per guidelines, baseline is 3 when coverage is high. The description does not add any parameter semantics since there are none to explain.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' and resource 'image sizes and resolution options for Seedream'. It clearly distinguishes from sibling tools like seedream_generate_image and seedream_list_models.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description includes a 'Use this when' section listing three clear scenarios. While it doesn't explicitly state when not to use it or mention alternatives, the guidelines are adequate for an agent to understand when to invoke this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.16seedream_edit_image2 fields changedInput schema / properties / model / defaultPrevious value: -"doubao-seedream-5-0-260128"New value: +"doubao-seedream-5-0-lite-260128"Input schema / properties / model / enumPrevious value: -[
- "doubao-seedream-5-0-pro-260628",
- "doubao-seedream-5-0-260128",
- "doubao-seedream-4-5-251128",
- "doubao-seedream-4-0-250828"
-]New value: +[
+ "doubao-seedream-5-0-pro-260628",
+ "doubao-seedream-5-0-lite-260128",
+ "doubao-seedream-4-5-251128",
+ "doubao-seedream-4-0-250828"
+]seedream_generate_image4 fields changedInput schema / properties / model / defaultPrevious value: -"doubao-seedream-5-0-260128"New value: +"doubao-seedream-5-0-lite-260128"Input schema / properties / model / descriptionPrevious value: -"Model to use for generation. 'doubao-seedream-5-0-pro-260628' (v5.0 Pro, flagship single image, highest quality; no sequential generation, streaming, or web search). 'doubao-seedream-5-0-260128' (v5.0 Lite, latest flagship, sequential generation, streaming, web search). 'doubao-seedream-4-5-251128' (v4.5, previous flagship, great quality). 'doubao-seedream-4-0-250828' (v4.0, stable, best value)."New value: +"Model to use for generation. 'doubao-seedream-5-0-pro-260628' (v5.0 Pro, flagship single image, highest quality; no sequential generation, streaming, or web search). 'doubao-seedream-5-0-lite-260128' (v5.0 Lite, sequential generation, streaming, web search). 'doubao-seedream-4-5-251128' (v4.5, previous flagship, great quality). 'doubao-seedream-4-0-250828' (v4.0, stable, best value)."Input schema / properties / model / enumPrevious value: -[
- "doubao-seedream-5-0-pro-260628",
- "doubao-seedream-5-0-260128",
- "doubao-seedream-4-5-251128",
- "doubao-seedream-4-0-250828"
-]New value: +[
+ "doubao-seedream-5-0-pro-260628",
+ "doubao-seedream-5-0-lite-260128",
+ "doubao-seedream-4-5-251128",
+ "doubao-seedream-4-0-250828"
+]Input schema / properties / tools / descriptionPrevious value: -"Optional list of tool types for the model to use during generation. Currently only 'web_search' is supported. Only supported by doubao-seedream-5-0-260128 (v5.0)."New value: +"Optional list of tool types for the model to use during generation. Currently only 'web_search' is supported. Only supported by doubao-seedream-5-0-lite-260128 (v5.0 Lite)."v0.1.15seedream_decompose_imageseedream_edit_image5 fields changedInput schema / properties / backgroundAdded value: +{
+ "anyOf": [
+ {
+ "enum": [
+ "transparent",
+ "opaque"
+ ],
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "description": "Seedream 5.0 Pro background mode. transparent requires one PNG input and PNG output.",
+ "title": "Background"
+}Input schema / properties / optimize_prompt_options / descriptionPrevious value: -"Optional prompt optimization configuration."New value: +"Prompt optimization. Pro supports standard/fast; Lite supports standard."Input schema / properties / size / anyOfPrevious value: -[
- {
- "enum": [
- "1K",
- "2K",
- "3K",
- "4K"
- ],
- "type": "string"
- },
- {
- "type": "null"
- }
-]New value: +[
+ {
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+]Input schema / properties / size / descriptionPrevious value: -"Output image resolution. '1K' (default), '2K', '3K', or '4K'."New value: +"Model-specific output size or explicit dimensions. Pro supports 1K/1.5K/2K; Lite supports 2K/3K/4K."Input schema / properties / streamRemoved value: -{
- "anyOf": [
- {
- "type": "boolean"
- },
- {
- "type": "null"
- }
- ],
- "default": null,
- "description": "Stream pictures progressively when supported.",
- "title": "Stream"
-}seedream_generate_image5 fields changedInput schema / properties / sequential_image_generation / descriptionPrevious value: -"Generate related images based on input. 'auto' enables it, 'disabled' (default) turns it off. Only supports v4.5 and v4.0 models."New value: +"Generate related images based on input. 'auto' enables it, 'disabled' (default) turns it off. Supported by Seedream 5.0 Lite, 4.5, and 4.0; not Pro."Input schema / properties / sequential_image_generation_options / descriptionPrevious value: -"Tunable options for grouped image generation. Only honored when `sequential_image_generation=auto`. Supports `max_images` (int, range [1, 15]). Only supported on doubao-seedream-4.5 and doubao-seedream-4.0."New value: +"Tunable options for grouped image generation. Only honored when `sequential_image_generation=auto`. Supports `max_images` (int, range [1, 15]). Supported by Seedream 5.0 Lite, 4.5, and 4.0; not Pro."Input schema / properties / size / anyOfPrevious value: -[
- {
- "enum": [
- "1K",
- "2K",
- "3K",
- "4K"
- ],
- "type": "string"
- },
- {
- "type": "null"
- }
-]New value: +[
+ {
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+]Input schema / properties / size / descriptionPrevious value: -"Output image resolution. '1K' (default), '2K', '3K', or '4K'. You can also specify custom dimensions like '1024x1024', '1280x720', etc."New value: +"Model-specific output size: Pro supports 1K/1.5K/2K (and auto for decomposition); Lite supports 2K/3K/4K. Explicit dimensions such as 2048x1024 are also accepted."Input schema / properties / streamRemoved value: -{
- "anyOf": [
- {
- "type": "boolean"
- },
- {
- "type": "null"
- }
- ],
- "default": null,
- "description": "Stream all pictures progressively. Default is false. Only supports v4.5 and v4.0 models.",
- "title": "Stream"
-}v0.1.14seedream_edit_image5 fields changedInput schema / properties / optimize_prompt_optionsAdded value: +{
+ "anyOf": [
+ {
+ "additionalProperties": true,
+ "type": "object"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "description": "Optional prompt optimization configuration.",
+ "title": "Optimize Prompt Options"
+}Input schema / properties / sequential_image_generationAdded value: +{
+ "anyOf": [
+ {
+ "enum": [
+ "auto",
+ "disabled"
+ ],
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "description": "Generate related images based on input. 'auto' enables it.",
+ "title": "Sequential Image Generation"
+}Input schema / properties / sequential_image_generation_optionsAdded value: +{
+ "anyOf": [
+ {
+ "additionalProperties": true,
+ "type": "object"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "description": "Tunable options for grouped image generation.",
+ "title": "Sequential Image Generation Options"
+}Input schema / properties / streamAdded value: +{
+ "anyOf": [
+ {
+ "type": "boolean"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "description": "Stream pictures progressively when supported.",
+ "title": "Stream"
+}Input schema / properties / toolsAdded value: +{
+ "anyOf": [
+ {
+ "items": {
+ "const": "web_search",
+ "type": "string"
+ },
+ "type": "array"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "description": "Optional list of tool types for the model to use during editing.",
+ "title": "Tools"
+}v0.1.11seedream_edit_image2 fields changedInput schema / properties / size / anyOfPrevious value: -[
- {
- "enum": [
- "1K",
- "2K",
- "3K",
- "4K",
- "adaptive"
- ],
- "type": "string"
- },
- {
- "type": "null"
- }
-]New value: +[
+ {
+ "enum": [
+ "1K",
+ "2K",
+ "3K",
+ "4K"
+ ],
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+]Input schema / properties / size / descriptionPrevious value: -"Output image resolution. '1K' (default), '2K', '3K', '4K', or 'adaptive'."New value: +"Output image resolution. '1K' (default), '2K', '3K', or '4K'."seedream_generate_image2 fields changedInput schema / properties / size / anyOfPrevious value: -[
- {
- "enum": [
- "1K",
- "2K",
- "3K",
- "4K",
- "adaptive"
- ],
- "type": "string"
- },
- {
- "type": "null"
- }
-]New value: +[
+ {
+ "enum": [
+ "1K",
+ "2K",
+ "3K",
+ "4K"
+ ],
+ "type": "string"
+ },
+ {
+ "type": "null"
+ }
+]Input schema / properties / size / descriptionPrevious value: -"Output image resolution. '1K' (default), '2K', '3K', '4K', or 'adaptive'. You can also specify custom dimensions like '1024x1024', '1280x720', etc."New value: +"Output image resolution. '1K' (default), '2K', '3K', or '4K'. You can also specify custom dimensions like '1024x1024', '1280x720', etc."v0.1.10seedream_edit_image5 fields changedInput schema / properties / guidance_scaleRemoved value: -{
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "default": null,
- "description": "Prompt weight — higher values make edits follow the prompt more closely. Range: [1, 10]. Default is 5.5 for doubao-seededit-3-0-i2i. Only works with v3 models.",
- "title": "Guidance Scale"
-}Input schema / properties / model / defaultPrevious value: -"doubao-seededit-3-0-i2i-250628"New value: +"doubao-seedream-5-0-260128"Input schema / properties / model / descriptionPrevious value: -"Model to use for editing. 'doubao-seededit-3-0-i2i-250628' (dedicated editing model, best for image modification). Other models can also be used for editing when images are provided."New value: +"Model to use for editing. Seedream 5.0 Pro, 5.0 Lite, 4.5, and 4.0 all support image editing when images are provided."Input schema / properties / model / enumPrevious value: -[
- "doubao-seedream-5-0-pro-260628",
- "doubao-seedream-5-0-260128",
- "doubao-seedream-4-5-251128",
- "doubao-seedream-4-0-250828",
- "doubao-seedream-3-0-t2i-250415",
- "doubao-seededit-3-0-i2i-250628"
-]New value: +[
+ "doubao-seedream-5-0-pro-260628",
+ "doubao-seedream-5-0-260128",
+ "doubao-seedream-4-5-251128",
+ "doubao-seedream-4-0-250828"
+]Input schema / properties / seedRemoved value: -{
- "anyOf": [
- {
- "type": "integer"
- },
- {
- "type": "null"
- }
- ],
- "default": null,
- "description": "Random seed for reproducible edits. Range: [-1, 2147483647]. Default is -1 (random). Only works with v3 models.",
- "title": "Seed"
-}seedream_generate_image4 fields changedInput schema / properties / guidance_scaleRemoved value: -{
- "anyOf": [
- {
- "type": "number"
- },
- {
- "type": "null"
- }
- ],
- "default": null,
- "description": "Prompt weight — higher values make the result more closely follow the prompt. Range: [1, 10]. Default is 2.5 for doubao-seedream-3-0-t2i. Only works with v3 models.",
- "title": "Guidance Scale"
-}Input schema / properties / model / descriptionPrevious value: -"Model to use for generation. 'doubao-seedream-5-0-pro-260628' (v5.0 Pro, flagship single image, highest quality; no sequential generation, streaming, or web search). 'doubao-seedream-5-0-260128' (v5.0 Lite, latest flagship, sequential generation, streaming, web search). 'doubao-seedream-4-5-251128' (v4.5, previous flagship, great quality). 'doubao-seedream-4-0-250828' (v4.0, stable, best value). 'doubao-seedream-3-0-t2i-250415' (v3 text-to-image, supports seed and guidance_scale). 'doubao-seededit-3-0-i2i-250628' is for image editing only — use seedream_edit_image instead."New value: +"Model to use for generation. 'doubao-seedream-5-0-pro-260628' (v5.0 Pro, flagship single image, highest quality; no sequential generation, streaming, or web search). 'doubao-seedream-5-0-260128' (v5.0 Lite, latest flagship, sequential generation, streaming, web search). 'doubao-seedream-4-5-251128' (v4.5, previous flagship, great quality). 'doubao-seedream-4-0-250828' (v4.0, stable, best value)."Input schema / properties / model / enumPrevious value: -[
- "doubao-seedream-5-0-pro-260628",
- "doubao-seedream-5-0-260128",
- "doubao-seedream-4-5-251128",
- "doubao-seedream-4-0-250828",
- "doubao-seedream-3-0-t2i-250415",
- "doubao-seededit-3-0-i2i-250628"
-]New value: +[
+ "doubao-seedream-5-0-pro-260628",
+ "doubao-seedream-5-0-260128",
+ "doubao-seedream-4-5-251128",
+ "doubao-seedream-4-0-250828"
+]Input schema / properties / seedRemoved value: -{
- "anyOf": [
- {
- "type": "integer"
- },
- {
- "type": "null"
- }
- ],
- "default": null,
- "description": "Random seed for reproducible results. Range: [-1, 2147483647]. Default is -1 (random). Only works with v3 models (doubao-seedream-3-0-t2i and doubao-seededit-3-0-i2i).",
- "title": "Seed"
-}v0.1.9seedream_edit_image1 field changedInput schema / properties / model / enumPrevious value: -[
- "doubao-seedream-5-0-260128",
- "doubao-seedream-5.0-lite",
- "doubao-seedream-4-5-251128",
- "doubao-seedream-4-0-250828",
- "doubao-seedream-3-0-t2i-250415",
- "doubao-seededit-3-0-i2i-250628"
-]New value: +[
+ "doubao-seedream-5-0-pro-260628",
+ "doubao-seedream-5-0-260128",
+ "doubao-seedream-4-5-251128",
+ "doubao-seedream-4-0-250828",
+ "doubao-seedream-3-0-t2i-250415",
+ "doubao-seededit-3-0-i2i-250628"
+]seedream_generate_image2 fields changedInput schema / properties / model / descriptionPrevious value: -"Model to use for generation. 'doubao-seedream-5-0-260128' (v5.0, latest flagship, highest quality). 'doubao-seedream-5.0-lite' (v5.0 economy variant, faster and lower cost). 'doubao-seedream-4-5-251128' (v4.5, previous flagship, great quality). 'doubao-seedream-4-0-250828' (v4.0, stable, best value). 'doubao-seedream-3-0-t2i-250415' (v3 text-to-image, supports seed and guidance_scale). 'doubao-seededit-3-0-i2i-250628' is for image editing only — use seedream_edit_image instead."New value: +"Model to use for generation. 'doubao-seedream-5-0-pro-260628' (v5.0 Pro, flagship single image, highest quality; no sequential generation, streaming, or web search). 'doubao-seedream-5-0-260128' (v5.0 Lite, latest flagship, sequential generation, streaming, web search). 'doubao-seedream-4-5-251128' (v4.5, previous flagship, great quality). 'doubao-seedream-4-0-250828' (v4.0, stable, best value). 'doubao-seedream-3-0-t2i-250415' (v3 text-to-image, supports seed and guidance_scale). 'doubao-seededit-3-0-i2i-250628' is for image editing only — use seedream_edit_image instead."Input schema / properties / model / enumPrevious value: -[
- "doubao-seedream-5-0-260128",
- "doubao-seedream-5.0-lite",
- "doubao-seedream-4-5-251128",
- "doubao-seedream-4-0-250828",
- "doubao-seedream-3-0-t2i-250415",
- "doubao-seededit-3-0-i2i-250628"
-]New value: +[
+ "doubao-seedream-5-0-pro-260628",
+ "doubao-seedream-5-0-260128",
+ "doubao-seedream-4-5-251128",
+ "doubao-seedream-4-0-250828",
+ "doubao-seedream-3-0-t2i-250415",
+ "doubao-seededit-3-0-i2i-250628"
+]v0.1.8seedream_edit_image1 field changedInput schema / properties / model / enumPrevious value: -[
- "doubao-seedream-5-0-260128",
- "doubao-seedream-4-5-251128",
- "doubao-seedream-4-0-250828",
- "doubao-seedream-3-0-t2i-250415",
- "doubao-seededit-3-0-i2i-250628"
-]New value: +[
+ "doubao-seedream-5-0-260128",
+ "doubao-seedream-5.0-lite",
+ "doubao-seedream-4-5-251128",
+ "doubao-seedream-4-0-250828",
+ "doubao-seedream-3-0-t2i-250415",
+ "doubao-seededit-3-0-i2i-250628"
+]seedream_generate_image2 fields changedInput schema / properties / model / descriptionPrevious value: -"Model to use for generation. 'doubao-seedream-5-0-260128' (v5.0, latest flagship, highest quality). 'doubao-seedream-4-5-251128' (v4.5, previous flagship, great quality). 'doubao-seedream-4-0-250828' (v4.0, stable, best value). 'doubao-seedream-3-0-t2i-250415' (v3 text-to-image, supports seed and guidance_scale). 'doubao-seededit-3-0-i2i-250628' is for image editing only — use seedream_edit_image instead."New value: +"Model to use for generation. 'doubao-seedream-5-0-260128' (v5.0, latest flagship, highest quality). 'doubao-seedream-5.0-lite' (v5.0 economy variant, faster and lower cost). 'doubao-seedream-4-5-251128' (v4.5, previous flagship, great quality). 'doubao-seedream-4-0-250828' (v4.0, stable, best value). 'doubao-seedream-3-0-t2i-250415' (v3 text-to-image, supports seed and guidance_scale). 'doubao-seededit-3-0-i2i-250628' is for image editing only — use seedream_edit_image instead."Input schema / properties / model / enumPrevious value: -[
- "doubao-seedream-5-0-260128",
- "doubao-seedream-4-5-251128",
- "doubao-seedream-4-0-250828",
- "doubao-seedream-3-0-t2i-250415",
- "doubao-seededit-3-0-i2i-250628"
-]New value: +[
+ "doubao-seedream-5-0-260128",
+ "doubao-seedream-5.0-lite",
+ "doubao-seedream-4-5-251128",
+ "doubao-seedream-4-0-250828",
+ "doubao-seedream-3-0-t2i-250415",
+ "doubao-seededit-3-0-i2i-250628"
+]v0.1.5seedream_edit_imageseedream_generate_imageseedream_get_taskseedream_get_tasks_batchseedream_list_modelsseedream_list_sizesv0.1.3seedream_edit_imageseedream_generate_imageseedream_get_taskseedream_get_tasks_batchseedream_list_modelsseedream_list_sizesv0.1.1seedream_generate_image2 fields changedInput schema / properties / optimize_prompt_optionsAdded value: +{
+ "anyOf": [
+ {
+ "additionalProperties": true,
+ "type": "object"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "description": "Optional prompt optimization configuration. Supports `mode` with values 'standard' (higher quality, slower) or 'fast' (quicker, lower quality). Only supported on doubao-seedream-4.5 (standard mode only) and doubao-seedream-4.0.",
+ "title": "Optimize Prompt Options"
+}Input schema / properties / sequential_image_generation_optionsAdded value: +{
+ "anyOf": [
+ {
+ "additionalProperties": true,
+ "type": "object"
+ },
+ {
+ "type": "null"
+ }
+ ],
+ "default": null,
+ "description": "Tunable options for grouped image generation. Only honored when `sequential_image_generation=auto`. Supports `max_images` (int, range [1, 15]). Only supported on doubao-seedream-4.5 and doubao-seedream-4.0.",
+ "title": "Sequential Image Generation Options"
+}v0.1.0seedream_edit_imageseedream_generate_imageseedream_get_taskseedream_get_tasks_batchseedream_list_modelsseedream_list_sizesScored across 7 tools
Each tool targets a clearly distinct operation: generate (text-to-image), edit (modify existing), decompose (split into layers), and the query/introspection tools. The single-vs-batch task querying pair (seedream_get_task vs seedream_get_tasks_batch) has an explicitly documented boundary, and list_models vs list_sizes cover different concerns.
Every tool follows a uniform seedream_ prefix plus a consistent verb_noun snake_case pattern (generate_image, edit_image, get_task, list_models). No mixing of conventions or casing styles.
Seven tools is well-scoped for an image generation service, with no redundant entries. Each tool maps to a distinct capability (three image operations, two query tools, two discovery tools).
Core lifecycle is covered: image creation, editing, decomposition, task status polling (single and batch), plus model and size discovery. Minor gaps exist around task management actions (e.g. cancel/delete task) and post-processing like upscaling, but the main workflows are fully supported.
AI video, images, music & SFX: Seedance 2.5, Veo 3.1, Kling 3.0, Nano Banana Pro, 20+ models.
Generate images, video, music, voice and 3D through one API. 30 tools, 200+ models.
Best Image and video generation: 20+ models (Kling, Seedance, Veo, NB, FLUX.2), OAuth, pay-per-use.
MCP server for ByteDance Seedance AI video generation
