uml-mcp-llm-visualizer git:20261105.4b281d9A

Immutable. This exact content never changes and is served at /api/v1/blob/a7f99a498cb96abb.

---
name: uml-mcp-llm-visualizer
description: Draw LLM and neural-network architectures in 2D and 3D (llm_2d, llm_3d).
---

# LLM visualizer

Follow `skill://uml-mcp-diagrams/SKILL.md`. Layer maps, autoencoder and GAN shapes, grouped N× blocks, and a rotatable 3D scene from one JSON source.

## Types

| Type | Use for | Example prompt |
| --- | --- | --- |
| `llm_2d` | a neural network or LLM architecture as a 2D map, or an autoencoder, VAE or GAN | Draw a transformer with encoder and decoder blocks repeated 6 times, top to bottom. |
| `llm_3d` | the same model as a rotatable 3D scene of glass layer panels | Show the transformer as a 3D scene I can rotate. |

## Steps

1. Check the live catalog (`list_diagram_types` or `uml://types`); the bundled plugins are on by default, but a server may turn them off with `plugins.bundled: false`.
2. Read the type's example from `uml://examples` and keep its field names.
3. Call `validate_uml`; an error names the field and, for a bad reference, lists the known ids, so fix it and validate again.
4. Render with `generate_uml_image` for a chat image, or `generate_uml` with `output_format: "html"` for the interactive page in the MCP App viewer. Clients without MCP Apps still get the PNG and SVG.
5. Pass `theme` (`auto`, `dark`, `light`) rather than editing colours.

## Example

```json
{"title":"Decoder-only transformer","subtitle":"Grouped view of a 7B parameter language model","theme":"dark","layers":[{"id":"tokens","label":"Token IDs","kind":"input","shape":[2048],"note":"BPE token sequence"},{"id":"embed","label":"Token embedding","kind":"embedding","shape":[2048,4096]},{"id":"attn","label":"Grouped-query attention","kind":"attention","shape":[32,128],"repeat":32,"note":"32 query heads, 8 key/value heads"},{"id":"ffn","label":"SwiGLU feed-forward","kind":"feedforward","shape":[4096,11008],"repeat":32},{"id":"norm","label":"RMSNorm","kind":"normalization","shape":[4096]},{"id":"logits","label":"Vocabulary logits","kind":"output","shape":[32000]}],"connections":[{"from":"tokens","to":"embed"},{"from":"embed","to":"attn","label":"hidden states"},{"from":"attn","to":"ffn","label":"residual stream"},{"from":"ffn","to":"norm"},{"from":"norm","to":"logits"},{"from":"embed","to":"norm","label":"residual path","style":"dashed"}]}
```