# snippai turns a screen region into LaTeX, Markdown or an explanation

> Snippai is a desktop snipping tool built on Electron, React, Tailwind and Radix UI whose interesting part is what it does with the captured image. It identifies formulas and converts them to LaTeX, extracts text, turns tables into Markdown, describes the image, solves problems posed in it, explains code snippets, detects predominant colours, and translates text in any language, with the model doing the work rather than a rule set.

**xyTom/snippai** — Snip Anything Solve Everything​

- Repository: https://github.com/xyTom/snippai
- Website: https://snippai.de/
- Stars: 1,938 · Forks: 133
- Language: TypeScript
- License: AGPL-3.0
- Published: 2026-10-16 · Updated: 2026-10-16 · Language: en
- Canonical page: https://hysenlabs.com/projects/xytom-snippai

## A snipping tool whose output is text

The description is short, Snip Anything Solve Everything, and the feature list is where the project actually lives. A conventional snipping tool copies a region of the screen to the clipboard and stops, and this one continues by looking at what it captured. The usage section says it plainly: you open the application, capture the desired region of your screen with the snipping tool, and Snippai will automatically analyze the captured image and provide relevant insights and conversions based on the detected elements. That word, detected, is the design, because the tool does not ask you what you want done with the image, it works out what kind of thing it is looking at and offers the matching conversion, so a screenshot of an equation and a screenshot of a table lead to different outputs without any input from you.

## Eight conversions, from LaTeX to translation

The features read as a list of models with different prompts. Formula recognition identifies formulas within images and converts them into LaTeX format, which makes it easier to work with mathematical expressions. Text extraction recognises and extracts text so it can be integrated into a workflow. Table conversion identifies tables and converts them into Markdown, for data manipulation and analysis. Image analysis analyses and describes the content, giving insight into visual elements. Problem solving solves various problems presented within images, using object recognition and pattern identification. Code understanding explains the functionality of code snippets found in images. Color detection identifies and extracts the predominant colours, useful for design analysis and image processing. And language translation translates and understands text in any language directly from an image, detecting the language and providing accurate translations in real time, for documents, signage and interfaces. The last item in the list is a promise rather than a feature, that more AI capabilities are coming.

## An Electron app assembled from four Vite configs

The build is Electron Forge with the Vite plugin, and the repository has four Vite configurations rather than one, which is how the main process, the preload script and the renderer are kept separate. There is vite.base.config.ts with the settings they share, vite.main.config.ts for the main process, vite.preload.config.ts for the bridge, and vite.renderer.config.ts for the window content, and forge.config.ts ties them to Electron Forge. The main entry in the package metadata is .vite/build/main.js, which is the output of that arrangement. The Forge makers cover the platforms a snipping tool has to exist on, with maker-deb for Debian, maker-rpm for Red Hat systems, maker-squirrel for Windows installers and maker-zip for a portable archive, and the auto-unpack-natives plugin alongside them. The presence of the fuses plugin and the electron/fuses package is the detail worth noting, because it means the packaged binary has its Electron flags rewritten, which is how a desktop app that reads your screen avoids shipping a browser with remote debugging enabled in a way anyone could attach to.

## The interface is Radix and Tailwind with a components.json

The front end is React with Tailwind and Radix UI, and the components.json file at the root is the giveaway about how the components are managed, since that file is the shadcn-style configuration that points at where the base components live and which theme they use. The dependency list shows the Radix primitives in use, with the dialog, label and popover packages among them, and the project is on Tailwind 3 with PostCSS and autoprefixer. The developer scripts are conventional. npm run start launches electron-forge start, and there is a separate start:web that runs vite alone, which is a useful arrangement because the interface can be worked on in a browser without the Electron shell. The packaging path is npm run package and npm run make, with publish for the release, lint for eslint over the TypeScript and TSX sources, and husky wired in as the prepare script for the git hooks. The docs are a VitePress site with its own dev, build and preview scripts.

## The version numbers and the release line do not match

There is a gap in the repository between the published releases and the package version, and it is worth understanding before you pin anything. The release tags are v0.3.5 on 2025-07-30, v0.5.0 on 2026-09-09 and v0.6.0 on 2026-10-06, while the version field in the package.json is 0.1.2, and the default branch is develop. A project that publishes installers from the releases page while the manifest carries a lower version is either versioning the artefacts separately from the package or has not caught the manifest up, and either way the safe move is to take the release you want from the releases page and read the notes rather than assuming the manifest version tells you what you installed. The download instructions point at the GitHub releases and the detailed installation instructions are in the documentation, and the site itself is snippai.de.

## Two different licences in the same repository

The licence information is contradictory and the contradiction is worth flagging rather than smoothing over. The repository is recorded as licensed under AGPL 3.0, and the README's acknowledgements section talks about the open-source libraries the project builds on and the sponsors who support it, with Fastly donating their services. The package.json in the same repository declares the license as MIT. Those are very different terms, and for a desktop application that reads your screen and sends images to a model, the choice of licence decides whether you may distribute a modified build. The other thing in the acknowledgements is a list of third-party projects, which is the part that is unambiguous, since the project uses various open-source libraries and technologies and thanks their developers and contributors.

## What this kind of tool is for, and what it needs

The honest way to assess it is as an OCR replacement with a model in the middle. That buys you things a rule based extractor cannot do, since a formula becomes LaTeX rather than a character soup, a table becomes Markdown rather than a grid of boxes, and a screenshot of code becomes an explanation. And it costs you the properties a rule based extractor has, since the output depends on a model and on a service, and the same image may not produce the same transcription twice, which matters if you are feeding the result into code or a formula. The README does not document which model the tool uses or how it is configured, so a team that cares about which data leaves the machine has to ask. The rest is a well-organised Electron application, with the build split into separate configurations, the packaging covering Linux, Windows and portable archives, a fuses plugin for the shipped binary, and a documentation site separate from the app.

## Conclusion

snippai is worth trying if you move information out of images every day, particularly if you deal with mathematical notation, tables in documents, or screenshots of code, since those are the cases where the model-based conversions save the most time. It is the wrong tool if you need pixel-exact or offline extraction, because the accuracy depends on a model and the results are not deterministic, and the wrong tool if you need a library, since this is a desktop application rather than a component you embed. Before you adopt it, check the licence situation, because the repository is recorded as AGPL 3.0 while the package metadata declares MIT, and that has to be settled before you ship anything built on it.

## FAQ

### What can snippai do with a captured screen region?

It identifies formulas and converts them to LaTeX, extracts text, converts tables to Markdown, describes the image, solves problems shown in it, explains code snippets, detects the predominant colours, and translates text in any language by detecting the language first.

### How is the snippai desktop app built?

With Electron Forge and the Vite plugin, using four Vite configurations, a base one plus separate ones for the main process, the preload script and the renderer, with forge.config.ts tying them together. Makers cover Debian, RPM, Windows installers and a portable zip, and the fuses plugin is used to rewrite the Electron flags in the shipped binary.

### What UI libraries does snippai use?

React with Tailwind and Radix UI primitives, with a components.json at the repository root in the shadcn style configuration. The docs are a separate VitePress site with its own dev, build and preview scripts, and husky is installed through the prepare script for the git hooks.

### Under which licence is snippai released?

The repository is recorded as AGPL 3.0 while the package.json declares MIT, so the two statements in the same project differ and need to be reconciled before you redistribute anything built on it. The acknowledgements credit the open-source libraries and technologies the project uses and the sponsors who support it, including Fastly.

## Sources

- [License: AGPL-3.0](https://github.com/xyTom/snippai/blob/develop/LICENSE)
- [Project website](https://snippai.de/)
- [README](https://github.com/xyTom/snippai/blob/develop/README.md)
- [Releases](https://github.com/xyTom/snippai/releases)
- [xyTom/snippai on GitHub](https://github.com/xyTom/snippai)

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Hysen Labs editorial analysis, written from the project's own repository and release notes. Cite the canonical page: https://hysenlabs.com/projects/xytom-snippai