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invokeai-mcp

invokeai-mcp

by sandraschi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

show_invokeai_dashboard_card

Display InvokeAI's version, queue, and model counts in a single rich card. Monitor the engine's status at a glance.

Instructions

Show InvokeAI fleet status (version, queue, model counts) as a rich card.

Return Format

ToolResult with PrefabApp card; plain text fallback in content.

Examples

show_invokeai_dashboard_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_dashboard_card"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations, the description carries full behavioral disclosure burden. It does disclose the return format (PrefabApp card, plain text fallback), but it does not explicitly state that the operation is read-only or side-effect-free. The verb 'Show' implies non-mutating, but this is not stated.

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 succinct and well-structured: a clear purpose sentence, a brief return format note, and an example. Every sentence earns its place with no redundancy.

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?

For a zero-parameter display tool with no output schema, the description is complete enough. It specifies what the card shows, the return format, and provides an invocation example, leaving no ambiguity about usage or expected results.

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 and an empty schema, so the description cannot add parameter-level detail. According to the rubric, 0 parameters gets a baseline of 4; no additional explanation is needed.

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 uses a specific verb ('Show') and clearly identifies the resource ('InvokeAI fleet status') along with the content covered (version, queue, model counts). This distinguishes it from sibling card tools (queue, gallery, models) by indicating it is the overall dashboard view.

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?

There is no explicit statement about when to use this tool versus alternatives. However, the scope 'fleet status' and the 'dashboard' name imply it is for overall status overviews, which provides indirect guidance but no clear exclusions 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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