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MCP Fooocus API

MCP Fooocus API

by raihan0824
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

list_available_styles

Retrieve available image generation styles from the MCP Fooocus API to select appropriate visual themes for AI art creation.

Instructions

List all available styles for image generation.

Returns:
    Dictionary containing all available styles organized by category

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": "list_available_styles"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool lists styles and returns a dictionary organized by category, which is helpful. However, it lacks details on potential side effects, error conditions, or performance aspects (e.g., caching, rate limits), leaving gaps in behavioral understanding.

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 extremely concise and well-structured: the first sentence states the purpose, and the second clarifies the return format. Every sentence adds value without redundancy, making it front-loaded and efficient.

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 the tool's low complexity (0 parameters, no annotations, but has an output schema), the description is reasonably complete. It explains what the tool does and the return format, and the output schema likely covers return values in detail. However, it could benefit from more behavioral context or usage guidance to be fully comprehensive.

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 input schema has 0 parameters with 100% coverage, so the schema fully documents the lack of inputs. The description doesn't add parameter details, which is unnecessary here. A baseline of 4 is appropriate for zero-parameter tools, as no compensation is needed.

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?

The description clearly states the tool's purpose: 'List all available styles for image generation.' It specifies the verb ('List') and resource ('available styles for image generation'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'generate_image' or 'get_server_info', which would be needed for a score of 5.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'generate_image' (which might use styles) or 'get_server_info', nor does it specify prerequisites or contextual triggers. This leaves the agent without usage direction.

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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