Skip to main content
Glama

meshy_to_bottube

Converts a text prompt into a 3D model turntable video and publishes it to BoTTube.

Instructions

One-shot: prompt -> Meshy 3D -> turntable -> video -> BoTTube upload.

Preflights every dependency up front (so a missing Blender/ffmpeg/key can't waste a billed Meshy generation), then runs the whole pipeline in a single working directory.

Always returns a dict. On success: ok=True plus watch_url / watch_url_full and every intermediate path. On a known stage failure: ok=False with error / failed_stage and whatever artifacts were produced before the failure (so nothing is silently lost).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYes
titleYes
descriptionNo
tagsNo3d,meshy,turntable
categoryNo
art_styleNorealistic
should_remeshNo
texture_promptNo
enable_pbrNo
framesNo
resolutionNo
fpsNo
durationNo
timeoutNo
Behavior5/5

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

With no annotations provided, the description fully bears the burden. It discloses preflight dependency checks, single working directory usage, return dict structure, success/failure details, and artifact preservation. This is comprehensive behavioral disclosure.

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 extremely concise for the complexity, using bullet points and short sentences. It front-loads the pipeline summary and then adds essential behavioral details without 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 14 parameters and no output schema, the description covers the return value well and explains the pipeline flow. However, it lacks parameter semantics and could include a note on required inputs. Still, it is largely complete for a complex tool.

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

Parameters2/5

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

The description adds no information about the 14 parameters beyond the schema. With 0% schema description coverage, the description should compensate by explaining key parameters like art_style, texture_prompt, frames, etc., but it does not.

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 purpose: a one-shot pipeline from text prompt to BoTTube upload, passing through Meshy 3D, turntable rendering, and video generation. It distinguishes itself from sibling tools by combining multiple steps into a single invocation.

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 implies when to use this tool (for a full pipeline) and provides behavioral context (preflights, error handling). However, it does not explicitly contrast with alternatives like using individual steps, but the unique combination makes the use case clear.

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/Scottcjn/meshy-bottube-mcp'

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