Skip to main content
Glama
kevintsai1202

muse-image-mcp

by kevintsai1202
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

Muse 對話式迭代修圖

iterate_image

Modify images through multi-turn conversational prompts, returning a response_id to continue editing via previous_response_id. Costs $0.01 per image.

Instructions

以對話方式多輪迭代修改圖片。回傳中一定包含 response_id；下一輪修改時把它填入 previous_response_id 即可延續同一段對話，本 server 不保存任何對話狀態。每張圖片成本 US$0.01。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNo模型 ID，省略則使用伺服器設定的預設模型
imagesNo首輪參考圖，本機路徑或 http(s) 網址
promptYes本輪的修改指令
extra_paramsNo傳給 API 的額外參數（物件），用於新模型的特殊參數。會與伺服器全域設定合併，單次設定優先。與請求核心欄位（model、prompt、response_format 等）衝突的 key 會被忽略並在回應中提示。
filename_prefixNo輸出檔名前綴，預設 muse-iter
reasoning_strengthNo推理強度，預設 high
previous_response_idNo上一輪回傳的 response_id；省略代表開始一段新對話

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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 usefully discloses statelessness, the response_id/previous_response_id continuation mechanism, and cost per image, though auth/rate limits and full return behavior are not covered.

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?

Three sentences, front-loaded with purpose, then continuation mechanics, then cost. No filler or redundant framing.

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

Completeness3/5

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

No output schema exists, yet the description only states that response_id is always included and does not explain the image output or other return fields. For a seven-parameter tool with nested extra_params and no annotations, this leaves meaningful gaps.

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

Parameters3/5

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

Schema description coverage is 100%, so all seven parameters are already documented in the schema. The description restates the previous_response_id workflow and cost but adds little parameter-specific semantics beyond the schema.

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

Purpose4/5

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

States a specific verb and resource: 多輪迭代修改圖片. The multi-round iterative scope implicitly distinguishes it from generate_image and edit_image, but no sibling is named explicitly.

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

Usage Guidelines3/5

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

No explicit when-to-use or when-not-to-use guidance versus generate_image or edit_image. The multi-round dialogue context is implied by the description but not framed as routing guidance.

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

Deploy Server

Other Tools