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novelai-mcp

novelai-mcp

by DesmondFox
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

novelai_upscale

Increase image resolution and clarity with NovelAI's neural upscaler. Input an image path to produce an upscaled version.

Instructions

Upscale an image with NovelAI's neural upscaler.

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_path": "<image_path>"
    },
    "name": "novelai_upscale"
  }
}

Input Schema

NameRequiredDescriptionDefault
modelNonai-diffusion-5-full
image_pathYes
output_dirNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior2/5

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 only states the core action and does not reveal side effects, output behavior, output location semantics, or any requirements/limitations. The agent learns what the tool does but not how its behavior manifests beyond that.

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 a single front-loaded sentence with no filler. Every word earns its place, and the primary action is stated immediately.

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

Completeness2/5

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

For a tool with no annotations, no output schema, and 3 parameters, the description is too thin. An agent is not told what the tool returns, whether it writes to output_dir, what happens when output_dir is null, or what model options are available. The basic purpose is clear, but the operational envelope is incomplete.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for the missing parameter documentation, but it does not. The schema gives titles and a default model value, but the model value 'nai-diffusion-5-full' and the meaning of output_dir null are unexplained. 'Image Path' is self-evident from its title, giving only marginal semantic value.

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 states a specific verb ('upscale') with a specific resource ('an image') and names the provider ('NovelAI's neural upscaler'). It is immediately distinguishable from sibling tools like novelai_generate_image or novelai_inpaint, which clearly do different operations.

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?

The description implies the obvious use case: use when an image needs to be upscaled. However, it provides no explicit guidance about when to prefer this tool over siblings, nor any exclusions or alternative routing.

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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