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Blender MCP Ultra

Blender MCP Ultra

by 3bdull4h2008
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

align_object

Align an object's position, rotation, or scale to match a target reference object. Choose which transforms to align: location, rotation, or scale.

Instructions

Align one object's transform to another.

Args: name: Object to align. target: Reference object. align_location: Match position. align_rotation: Match rotation. align_scale: Match scale.

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": {
      "name": "<name>",
      "target": "<target>"
    },
    "name": "align_object"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameYes
targetYes
align_scaleNo
align_locationNo
align_rotationNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.0.0

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral burden. It explains that align_location, align_rotation, and align_scale match the target's corresponding properties, but it does not disclose whether the operation modifies the object in place, uses world vs. local coordinates, or how errors are handled. Some behavioral info is present, but not comprehensive.

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, with a one-line summary followed by a clear list of arguments. It is front-loaded with the main purpose and contains no extraneous information, making it easy to scan.

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?

The description covers the tool's purpose and all parameters, which is sufficient for calling it correctly. However, it lacks usage guidance and some behavioral details (e.g., world vs. local transforms, side effects). For a simple alignment tool, this 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.

Parameters5/5

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

Schema description coverage is 0%, but the description explicitly explains each parameter: name (object to align), target (reference object), and the three alignment booleans with their meanings. This fully compensates for the lack of schema descriptions, providing clear parameter semantics.

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 action ('align') and resource ('one object's transform to another'), making it clear what the tool does. It distinguishes from siblings like move_object, rotate_object, and scale_object by indicating a combined alignment operation rather than a single-axis transform.

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 explicit guidance on when to use this tool versus alternatives such as set_object_transform or snap_to_cursor. The description does not mention exclusions, prerequisites, or recommend this over other tools, leaving usage context implicit.

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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