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volcengine-seedream-img-mcp

volcengine-seedream-img-mcp

by ckz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

generate_image_group

Generate multiple related images from a single text prompt, optionally using reference images to guide style or content.

Instructions

Generate a group of related images from a prompt and optional reference images. Returns a request_id to poll with get_image_result.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "prompt": "<prompt>"
    },
    "name": "generate_image_group"
  }
}

Input Schema

NameRequiredDescriptionDefault
imageNoOptional reference image(s). URL preferred. ref_count + max_images must be ≤ 15.
modelNoModel ID. All three models support group generation.doubao-seedream-4-5-251128
promptYesText prompt.
watermarkNo
max_imagesNoMax number of images to generate (not counting reference images).
resolutionNo2K
aspect_ratioNo1:1
response_formatNourl

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.2/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description carries full burden. It discloses async behavior (polling via request_id) but omits other behavioral traits like error handling, rate limits, or authorization needs. The mutation is not destructive, but transparency is incomplete.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (two sentences) and front-loaded with the primary action. However, it could be more information-dense by summarizing key parameter constraints (e.g., max 15 images) without adding length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (8 parameters, async, sibling tools), the description is incomplete. It lacks guidance on when to use it, does not summarize important constraints from the schema, and only hints at the return value (request_id) without mentioning other output details. No output schema exists, so more description is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50% (4 of 8 parameters have descriptions in schema). The description adds minimal: it mentions 'prompt' and 'optional reference images', but does not explain model, max_images, resolution, aspect_ratio, or response_format. It fails to compensate for the undocumented parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Generate a group of related images' and specifies the resources 'from a prompt and optional reference images'. It distinguishes from siblings like generate_image (single image) and edit_image, and mentions the async polling mechanism with get_image_result.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not provide explicit guidance on when to use this tool versus alternatives (e.g., generate_image for single images or edit_image for edits). It only implies usage for generating multiple related images, but lacks when-not-to-use or exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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