Zenith

Name: Zenith
Author: zenitheditor

by zenitheditorversion 0.0.8i★ –iRuns on your computer

Registry nameio.github.zenitheditor/zenith

Install

Overview

Description from the maker (original English)

Author, validate, edit, and render deterministic .zen design docs to PNG/PDF.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Design, images & audio

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "zenith": {
      "command": "npx",
      "args": [
        "-y",
        "@zenitheditor/zenith-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add zenith -- npx -y @zenitheditor/zenith-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "zenith": {
      "command": "npx",
      "args": [
        "-y",
        "@zenitheditor/zenith-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "zenith": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@zenitheditor/zenith-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account zenitheditor, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Design, images & audioi

More stars than 0% of the other 2184 servers in this category
Published to the registry more recently than 14% of the other 2184 servers in this category
Basic checks equal to or better than 100% of the other 2184 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Zenith safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.0.8) reached the registry 4 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Figma Context MCP

by GLips

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

Runs on your computer★ 16,165MITUpdated 5 months ago

Install

Claude Real Video

by HUANGCHIHHUNGLeo

Let any LLM watch a video locally — and search everything it has ever watched.

Runs on your computer★ 2,284MITUpdated 2 months ago

Install

Figma MCP Server

by figma

Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.

Runs in the cloud★ 2,152Updated 13 months ago

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Zenith

A design-document format and engine built for the age of AI agents.

Plain-text .zen design files that you can read, diff, review, validate, and let an agent safely edit — compiled deterministically to pixel-exact PNG, self-contained SVG, and print-ready PDF.

Install Quick start Features Validation Commands Agents

Every banner and diagram in this README is itself created using Zenith — source in assets/showcase/ .

Zenith is a plain-text format and engine for design files — posters, decks, books, social graphics, diagrams, and more. The idea is simple: design should work the way code does. You should be able to read it, diff it, review it, test it, and let an agent safely edit it.

A .zen file is human-readable KDL text. The engine parses it, validates it against a large diagnostic set, compiles it to a backend-neutral scene, and renders the same file to the same pixels every time — as a PNG, self-contained SVG, or print-ready PDF.

The sections below are collapsed to keep this page skimmable — click any heading's ▸ to expand it. Install and Quick start are open by default.

Install

The recommended way to install the zenith CLI is the install script, which detects your platform and downloads the matching prebuilt binary from GitHub Releases.

Linux / macOS

curl -fsSL https://raw.githubusercontent.com/zenitheditor/zenith/main/scripts/install.sh | sh

Windows (PowerShell)

irm https://raw.githubusercontent.com/zenitheditor/zenith/main/scripts/install.ps1 | iex

Set ZENITH_INSTALL_DIR to change the install location (default ~/.local/bin):

ZENITH_INSTALL_DIR=/usr/local/bin \

curl -fsSL https://raw.githubusercontent.com/zenitheditor/zenith/main/scripts/install.sh | sh

With cargo

cargo install zenith-tool    # from crates.io (installs the `zenith` binary)

cargo install --git https://github.com/zenitheditor/zenith zenith-tool # from source

Thirteen library crates are published under their own names for Rust projects that build on the engine directly: zenith-geometry, zenith-session, zenith-core, zenith-layout, zenith-raster, zenith-scene, zenith-perception, zenith-zpx, zenith-render, zenith-tx, zenith-producers, zenith-pipeline, and zenith-editor. zenith-editor-wasm and zenith-editor-bench are not published.

With npm

npm install -g @zenitheditor/zenith-mcp

npx -y @zenitheditor/zenith-mcp --help

The npm package installs the matching prebuilt zenith binary from GitHub Releases and is focused on the MCP Registry launch path. The unscoped zenith binary remains the Rust CLI.

GitHub Releases

Download directly from GitHub Releases:

Platform	Architecture	Asset
Linux	x86_64	`zenith- -linux-x64.tar.gz`
Linux	aarch64	`zenith- -linux-arm64.tar.gz`
macOS	x86_64	`zenith- -macos-x64.tar.gz`
macOS	Apple Silicon	`zenith- -macos-arm64.tar.gz`
Windows	x86_64	`zenith- -windows-x64.zip`

Update

zenith update                   # latest stable release

zenith update --pre # latest prerelease zenith update --version # a specific release tag, e.g. the ones on the Releases page

Verify with zenith --version.

Build from source

For local development or source installs:

git clone --recurse-submodules https://github.com/zenitheditor/zenith

cd zenith cargo build --release cargo install --path zenith-cli # installs zenith to ~/.cargo/bin ./scripts/install.sh --local # installs the local build to ~/.local/bin

The release binary lands at target/release/zenith. No C toolchain or system libraries are required — the dependency graph is C-free and unsafe is forbidden workspace-wide.

Quick start

zenith validate examples/hello.zen          # report diagnostics (add --json for machine output)

zenith fmt examples/hello.zen # canonical, idempotent formatting zenith fix draft.zen --apply # apply machine fixes (tokens, typos) in one step zenith tokens examples/hello.zen # list design tokens and their resolved values zenith inspect examples/hello.zen # print the node tree (read-only) zenith render examples/hello.zen --png hello.png # render to PNG

zenith render examples/multipage.zen --all-pages out/ # one PNG per page zenith render examples/hello.zen --pdf hello.pdf # print-ready PDF zenith render examples/hello.zen --svg hello.svg # self-contained SVG zenith render examples/multipage.zen --svg page.svg --page 2 zenith render examples/multipage.zen --all-pages-svg svg-pages/ zenith render examples/hello.zen --scene scene.json # dump the scene IR

Export flag	Output
`--svg OUT`	Page 1 by default, with outlined text.
`--pdf OUT`	Every page in one PDF by default.
`--page N`	Selects one page for single-output flags, including PDF.
`--all-pages-svg DIR`	Writes `page-N.svg` in document order.
`--raster-scale F`	SVG/PDF fallback resolution. Finite `0 < F <= 4`, default 1.
`--scale F`	PNG output scale. Finite `0 < F <= 4`, default 1.
`--deny render.svg_rasterized`	Blocks SVG exports requiring raster fallback.
`--deny render.pdf_rasterized`	Blocks PDF exports requiring raster fallback.

SVG assets: RGB colors and embedded image assets keep the artifact self-contained.
SVG text: Outlines preserve appearance and lose editing, selection, and search.
SVG fallback: Effects capture their complete scope. Non-normal blends capture the page. Crossed scopes and bitmap glyphs require capture.
PDF fallback: Unsupported features capture their required scope or page. Captured text loses selection and search. Captured links lose click targets.
Resolution: --raster-scale changes fallback pixels without changing vector geometry or page dimensions. Existing bitmap assets retain source resolution.
Reports: render.svg_rasterized and render.pdf_rasterized report pages, command ranges, and reasons. JSON includes structured rasterized regions.
PDF errors: CLI and MCP reject capture and resource errors. Legacy library APIs returning Vec retain compatibility emission. Use report APIs for strict errors.
Policy: Blocking diagnostics prevent output writes. Read the export report after source validation.
Writes: Each file uses a temporary sibling and rename. Write errors preserve existing destinations. Earlier committed outputs can remain after later I/O errors.
Batch reports: Partial rows and variants retain committed paths with failed status. Manifest write errors retain batch error counts.
Filesystem limits: Writes reject read-only destinations. Symlink outputs replace the resolved target and retain the link. Replacement preserves permissions and leaves other hard links unchanged. Crash durability is not guaranteed.

zenith render examples/multipage.zen --pdf book.pdf --raster-scale 2 --json

zenith render examples/hello.zen --svg hello.svg --raster-scale 2 --json

The smallest valid document:

zenith version=1 {

project id="proj.hello" name="Hello Zenith" tokens format="zenith-token-v1" { token id="color.bg" type="color" value="#f8fafc" token id="color.ink" type="color" value="#111827" token id="font.body" type="fontFamily" value="Noto Sans" token id="size.heading" type="dimension" value=(px)42 } styles {} document id="doc.hello" title="Hello Zenith" { page id="page.hello" w=(px)480 h=(px)160 { rect id="rect.bg" x=(px)0 y=(px)0 w=(px)480 h=(px)160 fill=(token)"color.bg" text id="text.hello" x=(px)24 y=(px)24 w=(px)432 h=(px)112 fill=(token)"color.ink" font-family=(token)"font.body" font-size=(token)"size.heading" { span "Hello Zenith" } } } }

See examples/ for runnable .zen files covering shapes, rich text, inline markdown (loaded from an external file), code blocks, images, frames/groups, multi-page documents and styles, plus the richer features — gradient, shadow, blur, filter, mask, table, flowchart (shapes + connectors), charts (bar/line/area/pie/donut/sparkline, with legends, value labels, and data binding), and anchors.

Why

Code got source control, types, tests, and PRs. Design files got none of that — and that hurts people and blocks AI.

Code got source control, types, tests, and pull requests. Design files got none of that. They're opaque blobs — you can't diff them, you can't review a change, and the same file can render differently on different machines.

That's a problem for people, and it's a bigger problem for AI. Agents can already write code and open pull requests, because code is text they can read and reason about. Drop them into a design tool and they go blind. Ask an agent to "make the heading brand red and tighten the layout" and there's nothing safe to grab onto — no stable target, no validation, no preview, no way to check the result.

Zenith fixes that. The goal is to make design files as safe to automate as code:

Plain text you own — readable, diffable, yours forever.
Stable IDs so every change is a reviewable patch, not a mouse drag.
Deterministic rendering — the same file always produces the same pixels.
Real validation — text fits, colors come from the design system, nothing falls off the page.
Safe edits — every change is a typed transaction, checked and previewable before it lands, with a source diff and an audit record.

It's not AI image generation

The opposite of an image model: Zenith generates the editable design , not a flat picture.

This is the most common mix-up, so it's worth being blunt: Zenith is the opposite of an image model like Nano Banana, ChatGPT image, or Grok Imagine.

An image ge

Only the beginning is shown; read the rest in the repo

Zenith

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Design, images & audioi

Common questions

Alternatives

Figma Context MCP

Claude Real Video

Figma MCP Server

README from the maker

Zenith

Install

With cargo

With npm

GitHub Releases

Update

Build from source

Quick start

Why

It's not AI image generation