Skip to main content
Glama
Reshvanth-Y

bottle-cap-mcp

by Reshvanth-Y

repair_mesh

Repair 3D meshes by removing non-manifold edges, filling holes, and unifying normals to create watertight, print-ready models from URLs or base64 input.

Instructions

Repair a 3D mesh (from Meshy image-to-3D or local CadQuery CAD) to make it manifold, watertight, and print-ready. Removes non-manifold edges/vertices, fills holes, unifies face normals, and optionally remeshes for clean topology. Accepts a URL (e.g. from generate_visual_mesh) or a raw base64-encoded mesh. Returns the repaired STL (or chosen format) as base64 plus a repair summary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNopublicly accessible URL of the mesh to repair (e.g. from generate_visual_mesh)
stlBase64Noraw mesh file (STL/OBJ/PLY) encoded as base64, for locally-generated meshes
inputFormatNofile format of the incoming mesh; used when writing the temp input filestl
repairLevelNohow extensively to repair the mesh; see field description for detailsstandard
outputFormatNoformat for the repaired output meshstl
targetFaceCountNotarget face count for remeshing pass (aggressive only); 0 = skip remesh
holeSizeThresholdNomax hole perimeter in faces to auto-fill; ignored for repairLevel conservative
Behavior4/5

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

With no annotations, the description covers key behaviors: removal of non-manifold edges, hole filling, normal unification, optional remeshing, and returning base64 + summary. It lacks details on side effects or limitations like potential detail loss.

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 two sentences, front-loaded with purpose, then input/output. Every sentence adds value; no redundancy.

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 7 parameters and no output schema, the description covers core functionality and input/output well. It could elaborate on repair levels and the repair summary, but overall is sufficiently complete for a complex 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?

All 7 parameters have schema descriptions (100% coverage). The tool description adds context on input sources and output format but does not significantly enhance parameter meaning beyond schema 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 description clearly states the tool repairs a 3D mesh to be manifold, watertight, and print-ready, listing specific actions. It distinguishes from siblings like generate_visual_mesh by mentioning it accepts output from that tool.

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 specifies input sources (URL from generate_visual_mesh or base64) and output (repaired STL plus summary). It implies when to use (need repair) but does not explicitly exclude scenarios or provide alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Reshvanth-Y/Team-Automata'

If you have feedback or need assistance with the MCP directory API, please join our Discord server