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Unreal-MCP

Unreal-MCP

by aadeshrao123
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get_statetree_bindings

Get property bindings with full path details from a StateTree asset. Optionally filter by a specific node GUID.

Instructions

Get property bindings with full path details. Each binding shows source/target node names, struct IDs, and property paths (e.g. "TargetLocation.X").

Optionally filter to bindings involving a specific node.

Args: asset_path: Content path to the StateTree asset node_guid: Only show bindings involving this node (optional)

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>"
    },
    "name": "get_statetree_bindings"
  }
}

Input Schema

NameRequiredDescriptionDefault
node_guidNo
asset_pathYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.2.1

TDQS

A4.4/5.0
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses that the tool returns bindings with source/target node names, struct IDs, and property paths. It implies read-only behavior via 'Get', but could be more explicit about side effects or permissions.

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 concise and well-structured, with a clear heading, an example, and bulleted parameter descriptions. No superfluous content.

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?

Given the tool has an output schema, the description does not need to explain return values. It covers the tool's purpose and parameters comprehensively, leaving no obvious gaps for an agent to use it correctly.

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

Parameters5/5

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

Schema coverage is 0%, but the description clearly explains both parameters: asset_path as the content path to the StateTree asset, and node_guid as optional filter. This adds crucial meaning beyond the raw schema.

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 it gets property bindings with full path details, with an example. It distinguishes itself from sibling tools like add_statetree_binding and remove_statetree_binding by being the retrieval counterpart.

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 explains the optional node filtering but does not explicitly state when to use this tool versus other StateTree retrieval tools or provide usage context like 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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