Meshy Openclaw logo

Meshy Openclaw

Organization
meshy-dev
meshy-openclaw

Generates 3D models, textures, format conversions, reference images, rigging, animation and motion clips with the Meshy CLI, and prepares them for physical 3D printing: white or multicolor prints, printability repair, Creative Lab products, sizing and slicer handoff (Bambu Studio, OrcaSlicer, PrusaSlicer, Cura). Use when the user asks to make, texture, rig, animate or convert a 3D model, or wants something 3D-printed. Signs in through the browser; no API key required.

Overview

Publishermeshy-dev
Repositorymeshy-3d-agent
Skill namemeshy-openclaw
Stars
106
Forks
24
Bundled files
7
LicenseMIT-0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 7 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by meshy-dev on GitHub. Read the source before you install it.

Installation

Install the Meshy Openclaw AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/meshy-dev/meshy-3d-agent/tree/main/skills/meshy-openclaw
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/meshy-dev/meshy-3d-agent.git /tmp/meshy-3d-agent
mkdir -p .claude/skills
cp -r /tmp/meshy-3d-agent/skills/meshy-openclaw .claude/skills/meshy-openclaw
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Meshy Openclaw in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Meshy Openclaw on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Meshy Openclaw is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Meshy 3D — Generation + Printing

Use Meshy CLI 0.7 (0.7.3 or later) to turn the user's request into a delivered asset: the requested files in the requested location, an inspected preview when one exists, and — for prints — the intended size, analysis/repair results and a slicer handoff when asked. Login or task submission alone is not completion. Choose the shortest suitable pipeline and reuse existing assets for follow-ups.

SECURITY MANIFEST

Executables: the Meshy CLI — meshy, or the pinned temporary package npm exec --yes --package=meshy-cli@0.7.3 -- meshy — plus npm to install it, node --version to check the runtime, and the file manager when the user asks to see a delivered file. No Python, no curl, no bundled scripts.

Credentials: the CLI's own browser sign-in (OAuth device flow) stores and refreshes a session in ~/.config/meshy/credentials.json (mode 0600). An existing MESHY_API_KEY, or an explicit --api-key-file, is honoured and takes precedence. The skill never reads, prints or copies a token, device code or key, and never asks for one in chat. MESHY_API_KEY is optional.

Network: the Meshy API (api.meshy.ai) and its sign-in page (www.meshy.ai), or api.meshy.cn and meshy.cn on the China site; the media hosts of assets being downloaded or input URLs being checked, without the credential; the npm registry when the CLI is installed or run as a temporary package.

Files: writes only inside one workspace per job — the directory the user named, or ./meshy_output — and the CLI refuses paths that escape it, including through symlinks. Existing files are not overwritten unless the user asked for it. Reads the input files the user pointed at and its own outputs in the workspace (previews, sidecars). Slicer handoff launches an already-installed slicer application.

Data leaving this machine: prompts, input images/models and task requests sent to Meshy.

Read what this request needs

NeedReference
CLI runner, sign-in, or output locationSetup
Digital assets: generation, texturing, remeshing, conversion, imagesPipelines
Rigging, animation, or generated motionAnimation
Physical prints: local preparation, print generation, analysis/repair, slicersPrinting recipes
Creative Lab products (figures, lamps, keychains, magnets, keycaps, fidgets)Creative Lab
Cost, waiting, preview, delivery, or finding a previous modelDelivery
Failed or uncertain operationTroubleshooting

Read the relevant section when needed; recipes are examples to adapt, not stages to run in full. An untextured model skips texturing; an existing GLB needs no conversion. Use command --help when parameters are uncertain.

Digital asset or physical print

Anything meant to be printed — a print, slicer, 3MF, STL, Bambu/Orca/Prusa/Cura, multicolor, a desk toy or a physical figure — follows Printing recipes from the first command, so generation parameters fit the print. Everything else follows Pipelines.

Print requestRoute
Scale, orient or ground an existing OBJLocal mesh prepare-print; no sign-in or balance
Open an existing STL or 3MFLocal slicer detect and slicer open; no sign-in or balance
White model from text or photoGeometry without textures; analyze/repair as needed; prepare the file
Multicolor modelGenerate/reuse geometry; analyze/repair as needed; texture; multi-color-print
Print in separate parts (build plate, colours per part, fewer supports)Generate/reuse geometry; auto-split; slice the parts
Check or fix an existing model (holes, thin walls), any formatFree analyze-printability by task ID or --model-url; repair only if needed
Resize an existing STL, 3MF or GLBScale it in the slicer; only an OBJ is resized locally
Creative Lab figure (a stylized collectible from a photo), vinyl figure, brick figure, lamp, keychain, fridge magnet, keycap or pixel fidget boardPrototype → review → build → select product artifacts
Creative Lab collapsible fidgetOne create from the photo → STL

Colour routes differ: multicolor paints one object's surface for a multi-material printer; a split cuts it into parts, one filament each, and drops the texture (split before any repair; the two do not chain); the pixel fidget board is a product of its own.

A figurine alone does not imply Creative Lab. Ask about size, color or style only when the missing choice materially changes the result.

First use and sign-in on OpenClaw

Before the first command run meshy --version; no need to ask. When meshy is missing or older than 0.7.3, install the newest 0.7.x with npm install -g meshy-cli@0.7 and say so in one line; Setup covers a refused install and a CLI of 0.8 or newer. Local-only print work stops there. Everything else reuses a verified auth status session; only when there is none, sign in:

  1. Start meshy auth login --device --format json --no-update-check (add --region cn for a user in mainland China) with exec and a short yieldMs (about 3000) and timeoutSeconds: 900, so it keeps running in the background and returns a sessionId.
  2. The CLI prints Enter code … at https://www.meshy.ai/device on stderr within seconds. If the first output holds only npm notices, process poll that same sessionId. Send the user the URL as a link and the code verbatim, plus what to do: open it, sign in to Meshy if asked, type the code, approve. Nothing needs to be sent back in chat.
  3. Do not start a second login, kill the session, or poll HTTP yourself; the CLI waits for the approval. When it exits, OpenClaw wakes this session; collect the result with process poll (a subagent, which gets no wake, polls before yielding). Then verify auth status and continue the original request with the inputs, path and budget already given.

A background session must not be detached with & or nohup. An expired or denied code means running the same login again; it never justifies re-running a paid task. Long wait commands behave the same way: let exec background them and resume from the completion wake, rather than re-submitting or looping on sleep.

Execution boundaries

  • Run API, upload, download and mesh operations through the CLI. Local inputs have a 50 MiB limit, and a local model must be GLB or glTF (rigging, UV unwrap and multicolor: GLB); use the supported URL input route for anything else.
  • Every command uses --format json --no-update-check and prints one meshy.cli/v1 envelope, auth included. Resolve WORKSPACE from the user's output path and pass it to every write.
  • Submit once with create --async, keep the owning resource and task ID, then wait on that task. Timeouts and unknown submissions follow Troubleshooting; they never authorize another paid create.
  • Work within the approved scope and budget; propose additional paid stages or reruns before spending. Local preparation and printability analysis are free; Delivery covers estimates.
  • Repair changes geometry and drops textures: use the repaired geometry downstream and retexture before multicolor output. Prepare a Y-up OBJ once, as a new file; never apply that transform to STL, 3MF or relief product output.

Deliver

Download only the needed assets. Send the user an available rendered preview as an image; a missing preview is stated, never implied, and a rendered PNG is not a 3D viewer. Report file paths, task IDs for follow-ups, and the actual charge. For prints also report dimensions and analysis/repair status; launch a detected slicer only when requested, and note that launch_requested does not prove the model was imported. Mention relevant remaining checks, such as supports and wall thickness, without calling an untested model guaranteed printable.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Meshy Openclaw AI skill do?

Generates 3D models, textures, format conversions, reference images, rigging, animation and motion clips with the Meshy CLI, and prepares them for physical 3D printing: white or multicolor prints, printability repair, Creative Lab products, sizing and slicer handoff (Bambu Studio, OrcaSlicer, PrusaSlicer, Cura). Use when the user asks to make, texture, rig, animate or convert a 3D model, or wants something 3D-printed. Signs in through the browser; no API key required.

Why use Meshy Openclaw on TypingMind?

Because you install it once and use it with any model. Meshy Openclaw is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Meshy Openclaw in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/meshy-dev/meshy-3d-agent/tree/main/skills/meshy-openclaw. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Meshy Openclaw?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Meshy Openclaw?

As many as you like. As long as a model supports skills, you can use Meshy Openclaw with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Meshy Openclaw AI skill free?

Yes. It is published on GitHub by meshy-dev under the MIT-0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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