Flathub Scraper - Linux Apps, Installs & Licences

Scrape the Flathub Linux app store in bulk. Extract app ID, name, developer, summary, description, monthly installs, favourites, licence, categories, architectures, verification status and timestamps to CSV/JSON. No API key.

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What does the Flathub Scraper do?

This Actor turns Flathub data into a structured dataset. You point it at the catalogue by popularity or newly added apps, it walks the result pages one after another, and it writes one clean row per app into your dataset — ready to export as JSON, CSV or Excel, or to pull straight from the Apify API.

Flathub is the app store for Flatpak and the default software source on most modern Linux desktops. Its keyless API publishes the number every other store keeps private — installs in the last month — alongside licence, categories and developer verification, which makes the export a usable picture of the Linux desktop market rather than a catalogue listing. Pagination is followed automatically until it runs out of results, hits your page limit or hits your Max items cap, whichever comes first. Every row is de-duplicated across the whole run, so you are never billed twice for the same app.

There is no API key, no login and no browser involved. That keeps runs fast and cheap, and it means you can schedule the Actor without worrying about credentials expiring.

Who is it for?

• Linux app developers sizing a category before building.
• Product teams measuring desktop Linux adoption of a tool class.
• Market researchers tracking open-source application uptake.
• Packagers and distributors auditing licences across a catalogue.
• Journalists and analysts covering the Linux desktop ecosystem.

Use cases

• Export the catalogue and rank apps by installs in the last month.
• Compare how crowded a category such as graphics or games already is.
• Find proprietary apps on an otherwise open-source store.
• Track which apps trend upward month over month.
• Audit which developers are verified and which are not.

Why use this Flathub Scraper?

• 🔑 Keyless — no account, no API token, no cookies to paste.
• 📦 28 fields per app — everything the source exposes, already typed.
• 📄 Real pagination — it walks page after page instead of returning the first screen.
• 🎯 Precise caps — Max items stops the run exactly where you want it, so the bill is predictable.
• 📊 Export anywhere — JSON, CSV, Excel or HTML, plus the Apify API and integrations.
• 💸 Pay per result — you pay for rows you actually receive, with no platform fees to calculate.

What data can you extract?

Every run produces one row per app, with these fields:

Field	Type	Description
appId	string	Reverse-DNS application ID, e.g. org.gimp.GIMP
name	string	Application name
summary	string	One-line summary
description	string	Full description with markup stripped
developerName	string	Developer or publisher name
appUrl	string	Flathub page for the app
installsLastMonth	number	Installations in the last month
favoritesCount	number	Number of users who favourited the app
trending	number	Flathub's trending score; negative means falling
projectLicense	string	Declared project licence
isFreeLicense	boolean	Whether the licence is a free-software licence
mainCategories	string	Primary categories, separated by a pipe
subCategories	string	Secondary categories, separated by a pipe
keywords	string	Keywords, separated by a pipe
architectures	string	Supported CPU architectures, separated by a pipe
runtime	string	Flatpak runtime the app builds against
appType	string	Entry type reported by Flathub
isMobileFriendly	boolean	Whether the app adapts to mobile form factors
isVerified	boolean	Whether the developer is verified
verificationMethod	string	How the developer was verified
verificationLogin	string	Verified account or organisation name
verificationWebsite	string	Website used for verification
iconUrl	string	Icon image URL
addedAt	string	When the app was added to Flathub
updatedAt	string	When the app was last updated
collection	string	Flathub collection this row came from
page	number	Result page the app appeared on
scrapedAt	string	ISO timestamp of extraction

Output example

{
  "appId": "org.vinegarhq.Sober",
  "name": "Sober",
  "summary": "Play, chat & explore on Roblox",
  "description": "Not affiliated with Roblox. Research project, use at your own risk. Read the notice on our website before using. We ported Roblox to Linux because they wouldn't. Enjoy millions of experiences on\u2026",
  "developerName": "VinegarHQ & Sober contributors",
  "appUrl": "https://flathub.org/apps/org.vinegarhq.Sober",
  "installsLastMonth": 201836,
  "favoritesCount": 357,
  "trending": -0.3881392106252708,
  "projectLicense": "LicenseRef-proprietary=https://sober.vinegarhq.org/notice.txt",
  "isFreeLicense": false,
  "mainCategories": "game",
  "subCategories": "GNOME | GTK",
  "keywords": "roblox | vinegar | launcher",
  "architectures": "x86_64",
  "runtime": "org.gnome.Platform/x86_64/50",
  "appType": "desktop-application",
  "isMobileFriendly": false,
  "isVerified": true,
  "verificationMethod": "website",
  "verificationLogin": null,
  "verificationWebsite": "vinegarhq.org",
  "iconUrl": "https://dl.flathub.org/media/org/vinegarhq/Sober/53a35f34cedfbd06c961a0f84bfb076f/icons/128x128/org.vinegarhq.Sober.png",
  "addedAt": "1743316841",
  "updatedAt": "1788638086",
  "collection": "popular",
  "page": 1,
  "scrapedAt": "2026-09-20T12:41:55.203Z"
}

How to use

Option A — the catalogue by popularity

{
  "collection": "popular",
  "maxItems": 2000,
  "maxPages": 40
}

1. Open the Actor and fill in the first field.
2. Set the page limit and Max items to bound the run.
3. Click Start, then export from the Output tab.

Option B — newly added apps

{
  "collection": "recently-added",
  "maxItems": 500,
  "maxPages": 10
}

Everything in the first field is processed independently, so you can batch several targets into one run and split them apart afterwards.

Input parameters

Parameter	Type	Default	Description
collection	string	popular	Which Flathub feed to walk.
maxPages	integer	10	How many result pages to walk for each collection.
maxItems	integer	500	Stop after this many apps.
maxConcurrency	integer	2	Parallel requests.
proxyConfiguration	object	{"useApifyProxy": true}	Proxy used to fetch pages.

Tips for best results

• Collection picks the feed: popular, trending, recently added or recently updated.
• Every collection covers the same catalogue of roughly 3,300 apps in a different order.
• Each page returns up to 50 apps, so a full sweep takes about 66 pages.
• installsLastMonth is the number that matters — almost no app store publishes it.
• trending is a score, not a count; negative values mean the app is losing ground.
• isFreeLicense false marks proprietary software distributed through Flathub.
• isVerified tells you the listing is controlled by the real upstream project.
• description is stripped of markup so it survives a CSV round trip.
• Schedule a monthly run and append to one dataset to build an install-count history.
• Pair with the Open VSX or npm scrapers to compare developer ecosystems.

Integrations

Send results straight into the tools you already use: Google Sheets, Slack, Zapier, Make, Airtable or any Webhook. You can also schedule the Actor to run hourly, daily or weekly and have each run append to the same dataset, which is how you build a price or availability history rather than a one-off snapshot.

API usage

Run the Actor and collect results from any language. Replace <YOUR_TOKEN> with your Apify API token.

cURL

curl -X POST "https://api.apify.com/v2/acts/logiover~flathub-app-scraper/run-sync-get-dataset-items?token=<YOUR_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"collection": "popular", "maxItems": 2000, "maxPages": 40}'

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_TOKEN>' });
const run = await client.actor('logiover/flathub-app-scraper').call({"collection": "popular", "maxItems": 2000, "maxPages": 40});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

from apify_client import ApifyClient

client = ApifyClient('<YOUR_TOKEN>')
run = client.actor('logiover/flathub-app-scraper').call(run_input={"collection": "popular", "maxItems": 2000, "maxPages": 40})
for item in client.dataset(run['defaultDatasetId']).iterate_items():
    print(item)

Use with AI agents (MCP)

This Actor is available through the Apify MCP server, so an AI agent can call it as a tool. Point your agent at https://mcp.apify.com and it can run the Flathub Scraper on demand — for example: "Pull the first 500 apps from Flathub and summarise what you find." The agent receives the same structured rows you would get from the UI.

FAQ

Do I need a Flathub account or API key?

No. The Actor reads publicly available data only. There is nothing to authenticate and no credentials to rotate.

How many apps can I get in one run?

As many as the source exposes. Raise the page limit and Max items together; the run stops at whichever limit it reaches first.

Why did I get fewer rows than I asked for?

The source ran out of apps. That is normal for narrow searches — broaden the query or add more targets to one run.

Are results de-duplicated?

Yes. Each app is emitted once per run, even when it appears on several pages, so you are never billed twice for the same record.

Why are some fields empty?

Flathub does not publish every attribute for every app. Empty means the source did not supply it, not that extraction failed.

What export formats are supported?

JSON, CSV, Excel, HTML and RSS from the Output tab, plus the Apify API and any integration you connect.

How fast is it?

It is pure HTTP with no browser, so a page of results typically takes a second or two. Raise Max concurrency carefully — the source rate-limits aggressive crawling.

Can I schedule it?

Yes. Use the Apify scheduler to run it on any interval and append each run to the same dataset for time-series analysis.

Does it work behind a proxy?

It uses Apify Proxy automatically. You can switch groups or supply your own proxies in Proxy configuration.

How often does the data change?

Flathub updates continuously. Re-run whenever you need current data; the Actor always reads the live source, never a cache.

Is the output schema stable?

Yes. Field names and types are fixed, so downstream pipelines will not break between runs.

What if the source changes its format?

Open an issue on the Issues tab and it gets fixed. The Actor is actively maintained.

Is it legal?

This Actor reads only publicly available data from Flathub — the same content any visitor or client sees without logging in. It does not bypass authentication, does not collect private data and does not attempt to defeat access controls. You are responsible for how you use the output: respect the source's terms of service, applicable copyright, and data-protection law such as GDPR where personal data is involved. Scraping public data is generally lawful in the EU and the US, but the responsibility for the downstream use of that data sits with you.

Related scrapers

• Firefox Add-ons Scraper — Browser extensions
• Google Play Data API — Android apps
• App Store Data API — iOS apps
• npm Package Intelligence — JavaScript packages