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Unreal-MCP

Unreal-MCP

by aadeshrao123
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add_niagara_component

Add a Niagara particle effect component to any actor in the Unreal Engine level by specifying the actor and Niagara system path.

Instructions

Add a NiagaraComponent to an existing actor in the level.

Args: actor_name: Name/label of the target actor system_path: Path to the Niagara System asset to assign component_name: Optional name for the component relative_location: Relative offset as "(X,Y,Z)" auto_activate: If true, auto-activate on begin play

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": {
      "actor_name": "<actor_name>",
      "system_path": "<system_path>"
    },
    "name": "add_niagara_component"
  }
}

Input Schema

NameRequiredDescriptionDefault
actor_nameYes
system_pathYes
auto_activateNo
component_nameNo
relative_locationNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.1

TDQS

B3.4/5.0
Behavior2/5

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

With no annotations, the description carries full burden for behavioral disclosure. It only states the action (adding a component) and lists parameters, but does not disclose side effects, permissions, or what happens if the actor doesn't exist. The description is minimal.

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 concise, starting with a clear purpose sentence, then listing parameters in a bullet-style format. It is front-loaded and avoids unnecessary verbosity. However, the parameter list could be integrated into a more streamlined paragraph.

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

Completeness3/5

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

The description covers the basic action and parameters but lacks context about the environment (e.g., actor must exist, system path validity, saving requirements). An output schema exists but is not shown; the description does not mention return values, which is acceptable since an output schema is present. Overall, it is adequate but not fully complete.

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% description coverage, so the description compensates by providing clear, human-readable explanations for each parameter (e.g., 'actor_name: Name/label of the target actor'). It adds semantic meaning beyond the schema's type and required flags, though it could specify formats or constraints like path type.

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's purpose: 'Add a NiagaraComponent to an existing actor in the level.' It specifies the verb, resource, and target, which distinguishes it from sibling tools like add_niagara_emitter or add_niagara_module.

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 guidance is provided on when to use this tool versus alternatives. The description lacks any mention of prerequisites, conditions, or exclusions. It only describes the parameters without contextual usage advice.

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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