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execute_blender_code

Destructive

Execute arbitrary Blender Python code to automate 3D workflows. Assign a result variable to capture output.

Instructions

Execute arbitrary Blender Python (bpy, bmesh, mathutils) on SuperMCP port 9877.

Assign result variable for return. Separate from Free's execute on 9876.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already flag destructiveHint=true, so the risk profile is covered. The description adds useful operational details: the target port and the requirement to assign a result variable for return. It does not discuss side effects, timeouts, or error handling, but the annotation plus the brief operating note keep this at a median score.

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?

Two sentences with no filler; the primary purpose is front-loaded and the port and differentiation are each given one clause. Every sentence earns its place.

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 a high-risk arbitrary-code execution tool with no output schema and minimal annotations, the description is thin. It omits return conventions beyond 'assign result variable', error handling, execution limits, and whether operations persist. An agent has enough to attempt a call but not enough to invoke it confidently in a production workflow.

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 zero description for the 'code' parameter, so the description carries the burden. It does specify allowed modules and the result-assignment requirement, which is genuinely useful. However, it never states the exact expected result variable name, return serialization, or how output/errors are delivered, so it only partially compensates for 0% coverage.

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 names a specific action ('Execute'), a clear resource ('arbitrary Blender Python (bpy, bmesh, mathutils)'), and a target ('SuperMCP port 9877'). It also distinguishes itself from Free's execute on 9876, so an agent can tell what it does at a glance.

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?

It provides context that this is the arbitrary-code path and explicitly separates it from Free's execute on 9876. However, it does not explain when to choose this over the many specialized Blender sibling tools (e.g., batch_execute_on_objects, mesh_operation), leaving usage largely implied.

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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