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volcengine-seedream-img-mcp

volcengine-seedream-img-mcp

by ckz
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

edit_image

Edit or restyle a reference image using a text prompt. Returns a request ID for polling results.

Instructions

Edit or restyle a single reference image using a text prompt (uses doubao-seededit-3-0-i2i). Output size is adaptive to input image aspect ratio. 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>",
      "image": "<image>"
    },
    "name": "edit_image"
  }
}

Input Schema

NameRequiredDescriptionDefault
imageYesReference image URL or base64.
promptYesEdit instruction.
watermarkNo
response_formatNourl

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

No annotations, so description bears full burden. Discloses output size adaptation to aspect ratio and polling mechanism via request_id. Names the underlying model. Does not cover auth, rate limits, or error handling, but adds significant context beyond schema.

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

Conciseness5/5

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

Two sentences, front-loaded with purpose and model, no wasted words. Efficiently conveys core information.

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

Completeness4/5

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

Given 4 params, no output schema, no annotations, the description covers purpose, model, adaptive output, and polling workflow. Lacks return format details and error handling, but is complete enough for typical use.

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%, but description adds no additional meaning beyond what the schema already provides (image URL, prompt, watermark, response_format). Does not elaborate on formats, constraints, or usage tips for 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?

States specific verb 'edit or restyle' and resource 'single reference image', uses text prompt, and names the model. Distinguishes from siblings (generate_image for generation, get_image_result for polling).

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

Usage Guidelines4/5

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

Clearly implies use case for editing existing images vs generating from scratch. Mentions returning request_id for polling, linking to sibling tool get_image_result. Lacks explicit when-not-to-use or alternatives.

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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