atx-mcp

Name: atx-mcp
Author: gridhra

by gridhraversion 0.6.7i★ –iRuns on your computer

Registry nameio.github.gridhra/atx-mcp

Install

Overview

Description from the maker (original English)

Deterministic, non-generative image transform MCP server: reproducible recipes, immutable originals.

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": {
    "atx": {
      "command": "npx",
      "args": [
        "-y",
        "atx-mcp",
        "--workspace",
        "your-value"
      ]
    }
  }
}

Run this in your terminal

claude mcp add atx -- npx -y atx-mcp --workspace your-value

This one needs values on its command line, so copy the settings and fill them in.

Or copy the settings yourself

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

{
  "mcpServers": {
    "atx": {
      "command": "npx",
      "args": [
        "-y",
        "atx-mcp",
        "--workspace",
        "your-value"
      ]
    }
  }
}

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 needs values on its command line, so copy the settings and fill them in.

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "atx": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "atx-mcp",
        "--workspace",
        "your-value"
      ]
    }
  }
}

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 gridhra, 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 2193 servers in this category
Published to the registry more recently than 73% of the other 2193 servers in this category
Basic checks equal to or better than 100% of the other 2193 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 atx-mcp 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 (0.6.7) reached the registry 12 days ago.

Which apps can use it?

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

What can I use instead?

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

Alternatives

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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

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

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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.

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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.

atx-mcp

English | 日本語 | 简体中文

A deterministic (non-generative) asset transformation MCP server for general-purpose AI agents, written in Rust.

It executes editing intent — "level the horizon, crop to 16:9, brighten it up a touch" — as a declarative transform recipe, and tracks every result as an immutable revision. The original asset is never modified.

Tilt correction + auto levels + a look applied (a fully deterministic recipe) — left: input / right: output.

See docs/DESIGN.md for the full design.

Use cases

Eye-catch image for an article

"Straighten this photo and crop it to a 16:9, 1600px eye-catch. WebP."

import_asset → detect_tilt (the AI skips correction when it's already near-level) → apply_transform (rotate → crop → resize → encode) → export_asset. The original is never touched, and the same recipe reproduces the same result every time.

Multiple sizes for social/CMS

"Generate the OGP, Instagram square, and thumbnail versions of this photo."

One original fans out into OGP 1200×630, Instagram 1080 square, and a 400px thumbnail in parallel. The same-recipe-same-revision idempotency means re-running never double-creates output; a one-word preset name works too.

Safe to publish

"Strip the location data for sure, but don't touch the colors."

strip_metadata (exif) removes EXIF including GPS while keeping the ICC profile intact. The AI can also warn ahead of time by checking has_gps from inspect_image.

Color and look adjustments

"Make just the sky bluer, leave everything else alone."

Covers curves / levels / hsl / white_balance, the film_soft preset, and importing your own .cube LUT with import_asset then applying it with lut.

Local (masked) adjustments

"Darken just the sky a bit, keep the ground as is."

generate_mask builds a mask (gradient, luminosity range, or hue range); after wiring it into the adjustment, render_preview with overlay:"mask" shows exactly where it will bite before you commit.

Layer compositing

"Blur a copy of this photo and blend it in at 50% screen for a soft glow."

The layers stack combines 16 blend modes, opacity, and masks to build reproducible composites like soft focus.

Watermarks, retouching, and perspective

"Stamp my logo in the corner, remove the power lines, and fix the converging verticals."

svg_overlay burns in a logo, clone/heal remove blemishes or wires by compositing both texture and tone, and perspective corrects converging verticals.

Reading documents (OCR pre-processing)

"Read this receipt photo for me." / "What does this slide say?"

detect_document finds the page or screen and returns a perspective quad ready to paste, the ocr_document preset (grayscale, auto levels, light sharpen) and trim concentrate the pixel budget on the text, and render_preview with long_edge:1568 hands the model an image it can actually read. No OCR engine is bundled: the model does the reading, atx only makes the pixels legible and reproducible. detect_text_blocks answers the question that decides the rest — "will this text survive the downscale, and where do I cut?" — by returning the text blocks in reading order plus ready-to-paste crop bands. threshold (Otsu / Sauvola) and ocr_binarize exist for external OCR engines.

Verification and accountability

"Show me this image before and after the edits, side by side."

compare_revisions places before/after side by side, or returns a difference heatmap with stats like mean_abs_diff. Every revision keeps its lineage, so the full edit history behind any image used in an article can be traced and reproduced — byte-identical on any machine.

Splitting one scan into separate images

"Two mounted sheets were scanned on one page. Save them as two files, keeping a little of the mount around each."

There is no split operation: the model runs one apply_transform per piece against the same source revision (crop to the left/right half, then trim to snap to the paper's edges with padding to keep some mount), and export_asset writes both at once. render_preview with no recipe and overlay:"grid" is how it reads the coordinates first.

What atx doesn't do — generative editing, RAW development, ML-based auto-cropping, OCR itself — is out of scope; see docs/DESIGN.md for the roadmap.

Install

atx-mcp is a single self-contained binary with no runtime dependencies. Pick one of the following.

1. cargo binstall (prebuilt binary, no compilation)

cargo binstall atx-mcp

claude mcp add --scope user asset-transform -- atx-mcp --workspace /path/to/asset-workspace

cargo-binstall downloads the release archive built by this repository's CI instead of compiling, so this is the fastest route for anyone who already has a Rust toolchain. (--scope user makes the server available in every project; omit it for the current project only.)

2. cargo install (builds from source)

cargo install atx-mcp

Works on any platform a Rust toolchain supports, including ones without a prebuilt binary. Needs a C compiler as well (libwebp is built from its vendored source).

3. Prebuilt binary (no Rust toolchain)

Installer scripts (default install location is ~/.local/bin, or %LOCALAPPDATA%\Programs\atx-mcp on Windows; the archive is verified against SHA256SUMS before extraction):

# macOS / Linux

curl -fsSL https://raw.githubusercontent.com/gridhra/atx-mcp/main/scripts/install.sh | sh

# Windows

irm https://raw.githubusercontent.com/gridhra/atx-mcp/main/scripts/install.ps1 | iex

To download manually, grab atx-mcp- - .tar.gz (.zip on Windows) from Releases. Supported targets:

Platform	Target triple
macOS (Apple Silicon)	`aarch64-apple-darwin`
macOS (Intel)	`x86_64-apple-darwin`
Linux x86_64	`x86_64-unknown-linux-musl` (statically linked, no glibc required)
Linux arm64	`aarch64-unknown-linux-musl` (statically linked, no glibc required)
Windows x86_64	`x86_64-pc-windows-msvc`

claude mcp add asset-transform -- ~/.local/bin/atx-mcp --workspace /path/to/asset-workspace

4. Docker

ghcr.io/gridhra/atx-mcp is a FROM scratch image holding the statically linked binary and nothing else (linux/amd64 and linux/arm64).

claude mcp add asset-transform -- \

docker run -i --rm -v "$PWD:/workspace" ghcr.io/gridhra/atx-mcp:0.6.7

Two things to keep in mind. `-i` is required: the server speaks the MCP stdio transport and needs stdin to stay open. And paths are container paths: the directory you bind-mount appears as /workspace inside the container, so import_asset and export_asset take paths like /workspace/photos/shot.jpg, not host paths.

5. npx (Node.js 18+, nothing to install)

The prebuilt native binary for your platform is pulled in automatically via optionalDependencies.

claude mcp add --scope user asset-transform -- npx -y atx-mcp --workspace /path/to/asset-workspace

Or add it directly to your MCP client config:

"mcpServers": { "asset-transform": { "command": "npx", "args": ["-y", "atx-mcp", "--workspace", "/path/to/asset-workspace"] } } }

--workspace (env: ATX_WORKSPACE) is the directory used as the asset store. It is created automatically if it doesn't exist.

--max-concurrent-tools (env: ATX_MAX_CONCURRENT_TOOLS) caps how many pixel-processing tool calls (import / inspect / detect_* / apply / preview / compare / mask) run at the same time; the default is the CPU count. Lower it on memory-constrained hosts. Tool work runs on dedicated threads, so the stdio transport (ping, cancellation, the vocabulary tools) stays responsive while images are being processed.

Tools (13)

Tool	Role
`list_operations`	Compact catalog of the recipe vocabulary: every operation with a one-line description and terse parameter hints, plus the built-in preset names. Optional `category:"geometry"\	"color"\	"filter"\	"output"` narrows it (read-only)
`explain_operation`	Full reference for one operation: parameter table (type, range, required/default, semantics), ready-to-paste JSON examples and gotchas. A built-in preset name works too and returns its full operation list. An unknown name returns the valid operations and presets, grouped (read-only)
`import_asset`	Import a local image into the workspace (sha256-idempotent). Takes `path` for one file or `paths` for a batch of up to 64 (a failing file does not abort the batch). Warns via `already_derived_from` when the bytes are already the output of a recipe in this workspace
`inspect_image`	Inspect dimensions, EXIF summary, ICC profile, presence of GPS data, luma statistics, a `sharpness` score (variance of the Laplacian — relative, so compare it against a known-good capture of the same subject) and a `perceptual_hash` (dHash, 16 hex digits) for "is this the same picture?". `include_exif:true` additionally returns every EXIF field as `{ifd, tag, value}` entries — off by default because the full dump can carry GPS coordinates and names (read-only)
`detect_tilt`	Estimate tilt angle via Canny+Hough (coarse) plus a projection profile (sub-0.1° refinement). Also returns horizontal/vertical family estimates; the full score curve is opt-in via `include_score_curve:true`. Returns "do not correct" when confidence is low (read-only)
`detect_document`	Find the dominant quadrilateral (page, screen, whiteboard, sign) via Canny + contours and return it as a `perspective`-ready `quad` (tl, tr, br, bl) with `confidence`, `area_ratio`, an `output_size_hint` and a paste-ready `suggested_operation`. Returns `quad:null` with a reason (`no_quad_found` / `already_rectified` / `low_confidence`) rather than guessing (read-only)
`detect_text_blocks`	Find the text-like blocks (headline, paragraphs, table, caption) via Otsu binarization + run-length smearing + connected components, in reading order, each with `line_count`, `median_line_height_px` and `ink_ratio`. `legibility.line_height_at_1568_px` says whether the text survives a downscale to long edge 1568 (below ~16px it usually does not), and `legibility.recommended_bands` splits the image into horizontal bands that clear that bar — each entry is already a `crop` operation to paste before `render_preview` (read-only)
`generate_mask`	Generate a deterministic grayscale mask (`linear_gradient` / `radial_gradient` / `luminosity_range` / `color_range`) as a PNG revision with the same dimensions as the reference image, to be referenced from an operation's `mask` field (idempotent)
`render_preview`	Apply a recipe (or a `preset`) at low resolution (long edge ≤768 by default, `long_edge` 256..1568 to hand a vision model a legible page) and return it as an inline image. `overlay:"grid"\	"thirds"\	"horizon" `overlays composition guide lines, and` overlay:"mask" `(with` mask_revision_id`) tints the coverage of a mask (drawn on the preview only; it has no effect on the actual transform). Also reports` estimated_vision_tokens`, a rough` width*height/750` budget for the returned image

| apply_transform | Apply a recipe (or a preset) at full resolution and pr

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

atx-mcp

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

atx-mcp

Use cases

Install

1. cargo binstall (prebuilt binary, no compilation)

2. cargo install (builds from source)

3. Prebuilt binary (no Rust toolchain)

4. Docker

5. npx (Node.js 18+, nothing to install)

Tools (13)