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invokeai-mcp

invokeai-mcp

by sandraschi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

show_invokeai_queue_card

Display the current generation queue status as a rich card, with a plain text fallback for easy monitoring.

Instructions

Show the generation queue status as a rich card.

Return Format

ToolResult with PrefabApp card; plain text fallback in content.

Examples

show_invokeai_queue_card()

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "show_invokeai_queue_card"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations, the description is the sole source of behavioral info. It discloses the output format (PrefabApp card with plain text fallback) but doesn't specify any side effects, permission requirements, or edge cases like empty queue.

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 appropriately concise and front-loaded, with a clear first sentence and a compact return-format note and example.

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?

For a zero-parameter, read-only display tool, the description covers purpose, output format, and usage example. It lacks detail about the card's content but is otherwise sufficient given the tool's simplicity.

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?

The tool has zero parameters, so the empty schema is fully covered. The description reinforces this with an example showing no arguments.

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 tool displays the generation queue status as a rich card, using a specific verb and resource. This distinguishes it from sibling card tools for gallery, models, and dashboard.

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?

No explicit when-to-use or comparison with alternatives is provided. The description only gives an example call, leaving the agent to infer when to choose this over other show_*_card tools.

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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