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MidjourneyMCP

MidjourneyMCP

by AceDataCloud
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

midjourney_get_seed

Retrieve the seed value of a generated Midjourney image to reproduce specific results or create variations with consistent randomness.

Instructions

Get the seed value of a previously generated Midjourney image.

The seed is a numeric value that controls the randomness of generation.
Using the same seed with the same prompt will produce similar results,
which is useful for reproducible generation or fine-tuning prompts.

Use this when:
- You want to reproduce a specific generation result
- You need the seed to use with --seed parameter in prompts
- You want to create variations with consistent base randomness

Returns:
    The seed value for the specified image.

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": {
      "image_id": "<image_id>"
    },
    "name": "midjourney_get_seed"
  }
}

Input Schema

NameRequiredDescriptionDefault
image_idYesThe ID of the generated image to get the seed for. This is the 'image_id' field from a previous imagine result.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.5
  2. Removedv0.1.4
  3. Addedv0.1.1

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It explains what a seed is and its role in reproducibility, and states the return value. It could mention that the operation is read-only and requires prior generation, but overall it's transparent.

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?

The description is concise with six well-structured sentences. Use cases are presented in a bullet-like format without redundancy, and every sentence contributes meaningfully.

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

Completeness5/5

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

Given the tool's simplicity (one required parameter, no nested objects, output schema present), the description fully covers the needed context: purpose, usage scenarios, parameter meaning, and return value. No gaps remain.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds value by clarifying 'image_id' as the field from a previous imagine result, which helps the agent understand the specific parameter context beyond the schema alone.

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 ('Get') and resource ('seed value of a previously generated Midjourney image'), making the tool's purpose unambiguous. It distinguishes from sibling tools like midjourney_imagine which generates images.

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?

The description provides explicit use cases (reproduce generation, use with --seed, create variations) but does not specify when not to use or mention alternative tools for similar tasks. It gives clear context for appropriate usage.

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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