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SekaiNoOwari77

mcp-3d-modeling-agent

blender_ai_mesh_remesh

Fix messy AI-generated meshes by retopologizing with VOXEL or SMOOTH methods, adjusting voxel size, octree depth, and smoothing to produce clean, usable topology.

Instructions

Retopologize a mesh using VOXEL or SMOOTH methods. Controls voxel size, octree depth, and smoothing. Useful for converting AI-generated meshes to clean topology.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
methodNoRemesh method (default: VOXEL)VOXEL
voxel_sizeNoVoxel size for VOXEL method - smaller = more detail (default: 0.05)
object_nameYesName of the mesh object to remesh
apply_smoothNoApply smoothing modifier after remesh (default: true)
octree_depthNoOctree depth for SMOOTH method (1-10, default: 5)
smooth_factorNoSmoothing strength (0.0-1.0, default: 0.5)
smooth_normalsNoSmooth normals after remeshing (default: true)
smooth_iterationsNoNumber of smoothing iterations (default: 2)

Schema Changelog

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

  1. First observedv0.4.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral burden. It clearly communicates the retopology operation and the controls involved, but it does not disclose that remeshing may destructively replace existing topology, UVs, or other mesh data, nor does it clarify how parameters interact when method is SMOOTH versus VOXEL.

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 three short, efficient sentences with the core operation front-loaded. Every sentence earns its place: what it does, what it controls, and when it is useful. No filler or redundancy.

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?

The description covers the core purpose and use case, and the schema covers parameters thoroughly. However, with eight parameters, no output schema, no annotations, and close sibling tools, the description lacks explicit guidance on method-parameter interplay (e.g., which parameters apply to VOXEL vs SMOOTH) and how to choose this tool over blender_sculpt_remesh_voxel.

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?

Schema description coverage is 100%, so the schema already documents all eight parameters with meaningful descriptions. The tool description adds only a high-level grouping (voxel size, octree depth, smoothing), which maps to the parameters but does not provide additional semantic value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Retopologize a mesh'), names the two methods (VOXEL or SMOOTH), and gives a clear use case ('converting AI-generated meshes to clean topology'). It does not explicitly distinguish this tool from the closely related blender_sculpt_remesh_voxel sibling, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a clear intended context: it is useful for AI-generated meshes that need clean topology. However, it does not mention when not to use it or name alternative tools such as blender_ai_mesh_cleanup or blender_sculpt_remesh_voxel, so it lacks explicit exclusion 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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