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Unreal-MCP

Unreal-MCP

by aadeshrao123
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add_input_action_modifier

Add a modifier such as DeadZone, Scalar, or Negate to an Input Action asset to customize input behavior.

Instructions

Add a modifier to an Input Action.

Args: asset_path: Path to the InputAction asset modifier_type: Class name — InputModifierDeadZone | InputModifierScalar | InputModifierNegate | InputModifierSwizzleAxis | InputModifierSmooth | InputModifierSmoothDelta | InputModifierScaleByDeltaTime | InputModifierResponseCurveExponential | InputModifierResponseCurveUser | InputModifierFOVScaling | InputModifierToWorldSpace properties: Optional modifier properties (e.g. {"LowerThreshold": 0.2, "Type": "Radial"})

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": {
      "asset_path": "<asset_path>",
      "modifier_type": "<modifier_type>"
    },
    "name": "add_input_action_modifier"
  }
}

Input Schema

NameRequiredDescriptionDefault
asset_pathYes
propertiesNo
modifier_typeYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.1

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It explains parameters but does not disclose side effects, whether changes are destructive, save behavior, or reversibility.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured with an Args section and is efficient. The list of modifier types is slightly verbose but necessary for clarity.

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?

Given no annotations and no output schema details in the description, the description lacks behavioral context and return value information. It is incomplete for safe and correct invocation.

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 0%, so description adds significant value. It clarifies asset_path as path, modifier_type with a list of valid classes, and properties with an example format.

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 'Add a modifier to an Input Action' with a clear verb and resource. It distinguishes from siblings like remove_input_action_modifier and add_input_action_trigger by specifying the action on modifiers.

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?

No explicit when-to-use or when-not-to-use guidance is given. The description implicitly suggests use for adding modifiers but does not mention alternatives or prerequisites.

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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