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Blender MCP Ultra

Blender MCP Ultra

by 3bdull4h2008
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

create_tree

Generate a procedural tree with customizable trunk, branches, and leaves for Blender scenes. Set trunk height, radius, branch levels, leaves per branch, and seed to create varied tree models.

Instructions

Generate a procedural tree with trunk, branches, and leaves.

Args: name: Object name. trunk_height: Height of the trunk. trunk_radius: Radius of the trunk. branch_levels: Number of branching levels. leaves_per_branch: Leaves per branch. seed: Random seed.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "create_tree"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameNoTree
seedNo
trunk_heightNo
trunk_radiusNo
branch_levelsNo
leaves_per_branchNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.0.0

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 the full behavioral burden. It states that a tree is generated, but it does not disclose whether the tool creates a new scene object, returns geometry data, produces a single mesh or separate parts, or has any side effects. A creation tool with zero annotations needs more behavioral context.

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 compact and front-loaded: one clear action sentence followed by a tidy parameter list. There is no redundant prose, and every line earns its place.

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?

All parameters are defined with defaults, making the tool callable as-is. However, with no annotations and no output schema, the description omits what the tool returns or how the result appears in the scene, and the usage-and-alternative gap further reduces completeness. It is adequate for a basic call but not fully self-sufficient.

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 description coverage is 0%, so the Args list meaningfully compensates by explaining all six parameters, including name, trunk dimensions, branch levels, leaves per branch, and seed. The explanations are still minimal and lack units or ranges, but they add real meaning beyond the schema's bare titles and defaults.

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 opening sentence states a specific verb and resource: 'Generate a procedural tree with trunk, branches, and leaves.' This makes the tool's purpose clear and distinguishes it from generic creation tools like create_object and other procedural generators like create_terrain or create_rock.

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?

The description gives no guidance about when to use this tool instead of alternatives such as create_object, create_terrain, or create_rock. It implies the use case by naming the resource, but it provides no context, exclusions, or selection criteria.

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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