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Blender Copilot MCP Server

by dwgx

build_scene_from_json

Build a complete Blender scene from a JSON description, generating and executing a bpy script in headless Blender.

Instructions

Build a complete Blender scene from a JSON description.

Generates a bpy script from the JSON and executes it in headless Blender. Adapted from CLI-Anything's scene building approach.

The JSON format supports:

  • materials: [{name, color, metallic, roughness}]

  • objects: [{mesh_type, name, location, rotation, scale, material, modifiers, collection, smooth}]

  • cameras: [{name, location, rotation, focal_length, active}]

  • lights: [{name, type, location, rotation, power, color, size}]

  • render: {engine, resolution_x, resolution_y, samples}

Example: { "materials": [{"name": "Red", "color": [1,0,0,1]}], "objects": [ {"mesh_type": "sphere", "name": "Ball", "location": [0,0,1], "material": "Red", "smooth": true, "modifiers": [{"type": "subdivision_surface", "params": {"levels": 2}}]} ], "cameras": [{"name": "Cam", "location": [0,-5,2], "rotation": [80,0,0], "focal_length": 85, "active": true}], "lights": [{"name": "Key", "type": "AREA", "location": [2,-2,3], "power": 200}] }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scene_jsonYes
blend_outputNo
render_outputNo
Behavior4/5

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

Since no annotations are provided, the description carries the full burden. It discloses that the tool generates a bpy script, executes it in headless Blender, and lists supported JSON fields. This gives good behavioral insight, though it does not cover error handling or potential side effects.

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 well-structured with bullet points and a concrete example, making it easy to parse. It is slightly long due to the example, but every section adds value; no redundant content.

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?

Given no output schema and no annotations, the description covers the tool's core operation (execution method, JSON structure). It lacks details on output parameters ('blend_output', 'render_output') and the scene handling (append vs clear), but is otherwise comprehensive.

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

Parameters3/5

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

The description elaborates extensively on 'scene_json' with a detailed example and field breakdown, compensating for the 0% schema coverage. However, 'blend_output' and 'render_output' are not explained, leaving ambiguity about their purpose and 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 clearly states 'Build a complete Blender scene from a JSON description', with a specific verb and resource. It distinguishes from siblings like 'generate_scene_script' by describing direct scene building rather than script generation.

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?

Usage is implied ('Build a complete Blender scene from a JSON description') but no explicit when-to-use vs alternatives like 'generate_scene_script' or 'io_import_file'. The mention of 'CLI-Anything' origins provides context but not comparative guidance.

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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