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Blender Antigravity MCP

Blender Antigravity MCP

by Cosmictraveler002
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

execute_blender_code

Run Python code in Blender to automate 3D operations. Break complex tasks into smaller steps for reliable reconstruction.

Instructions

Execute Python code in Blender. Break complex operations into smaller steps.

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": {
      "code": "<code>"
    },
    "name": "execute_blender_code"
  }
}

Input Schema

NameRequiredDescriptionDefault
codeYesPython code to execute

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.0.0

TDQS

C2.9/5.0
Behavior1/5

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

There are no annotations, so the description must carry the full burden of behavioral disclosure. It reveals nothing about side effects, persistence of changes, undo behavior, safety risks, Blender context availability, or whether arbitrary code can mutate scenes in irreversible ways.

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 short and front-loaded with the core purpose. The second sentence is mildly useful advice, but it is vague and does not add substance. Still, there is no redundant or bloated phrasing.

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

Completeness2/5

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

For an arbitrary code execution tool inside Blender, the description is incomplete. It does not mention return values, how results are communicated back, whether bpy is available, how errors are reported, or what execution context the code runs in. These are critical for an agent to reliably call the tool.

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 schema provides 100% coverage of the single parameter 'code' with the description 'Python code to execute'. The tool description adds no further meaning beyond the schema, so the baseline score of 3 is appropriate.

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 function: executing Python code in Blender. This is a specific verb-resource pair and is distinct from all sibling tools, which concern asset status, searches, downloads, and generation.

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 only a vague operational tip—'Break complex operations into smaller steps'—but does not explain when to choose this tool over the Blender-specific sibling tools, when not to use it, or what kinds of operations are appropriate for direct code execution.

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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