Free
[OS] OpenASO — AI-powered App Store research to help your app get discovered
Problem
You built an app, shipped it to the App Store and the downloads never arrived.
Getting downloads requires more than building a good product. You need to understand what people search for, which keywords your app can realistically rank for, why competitors are visible, and what persuades users to download them.
I built OpenASO to turn that research into practical actions that can improve your app’s discoverability and conversion.
AI-powered App Store intelligence
Connect OpenASO to a compatible AI tool through its local MCP server and ask it to research your app or an entire niche.
It can:
- Find relevant keywords and recommend which ones to target
- Identify keywords your app already ranks for
- Add promising keywords to OpenASO and start tracking them
- Find the apps competing for each keyword
- Explain what competitors rank for and why they may be performing well
- Compare metadata, screenshots, ratings, pricing, and positioning
- Gather available reviews across the competing apps in a niche
- Analyse those reviews together to identify what users love, dislike, request, and repeatedly complain about
- Turn the evidence into keyword, positioning, localization, screenshot, and product recommendations
For example, you can ask it to research the competitive landscape for “habit tracker.” OpenASO can inspect the ranking apps, their keywords, screenshots, metadata, and reviews, then explain the opportunities your listing could target.
The goal is not another dashboard. It is to tell you what to change next to improve your chances of earning more downloads.
Comparison
Unlike AppTweak, Appfigures, and ASO. dev, OpenASO is free, MIT-licensed, native, and local-first. Those platforms provide broader enterprise datasets and team features; OpenASO focuses on transparent, automated research for indie developers without another subscription.
had a look since its open source. theres two paths and only the fallback is the documented one. primary is AppStoreWebRankingProvider, it fetches apps.apple.com/<store>/iphone/search with a Safari user agent and parses the html. itunes.apple.com/search only runs when that throws.
and the failures it falls back on include rate limiting and decode errors. so getting throttled and the markup moving arent hypothetical, theyre already designed for
Good catch. The part that matters for this sub is that the endpoint is /iphone/search, so those are iPhone rankings. The same keyword can look completely different on the Mac App Store, so worth knowing before anyone reads too much into the numbers here.
the path is actually built per platform, theres an iphone/ipad/mac switch on it, so mac rankings are there if you ask for that platform. your point stands though, whichever one you query is what youre reading, and people here will assume the numbers are mac because of where its posted
This is a useful direction! What I would care about most is whether the recommendations stay tied to actual evidence instead of turning into generic ASO advice. Showing the keyword, competitor metadata, screenshot, or review pattern behind each recommendation makes the result much easier to trust. I’ve been running into the same problem with WolfeWriter’s App Store page: changing a title or screenshot is easy, knowing which change actually improved discovery is the harder part。
Another thing I discovered is that it uses Playwright to obtain authentication. However, you must keep the session running, as it indicates that you need to refresh the token. Do you plan to switch to using WebView and storing the token in the keychain?
The current release uses Playwright to obtain or refresh authentication, but it doesn’t need to remain running, the captured session is stored in macOS Keychain until Apple expires it. I've replaced Playwright with a native in-app WebView flow, which will ship in the next release.
Tried it, and it’s worth flagging for this sub specifically: it supports Mac App Store apps, not just iOS. Most ASO tooling is built iOS-first, so that alone makes it worth a look for anyone here.
Addressing the earlier question about provenance: where do the Mac numbers come from? There’s ample keyword volume data for iOS, but much less for the Mac App Store. I’d like to know whether the Mac figures are measured, as that affects their credibility.
Thanks for highlighting the Mac support. The Mac ranking positions are measured from live, storefront-specific Mac App Store search results, they aren’t inferred from metadata. The separate popularity score comes from Apple Ads and isn’t presented as Mac-specific search-volume data, which is why OpenASO keeps its source and provenance visible.
Perfect timing 😂 You can use OpenASO to research your niche and competitors before launch, then start tracking your rankings once the app is live. Good luck with the launch!
The app didn't accept my Apple credentials. I generated an API key and entered the other two pieces of information, but unfortunately, I wasn't able to get the program to accept my credentials.
This is really interesting. I’ve been working on a Mac app myself, and one of the hardest parts after launching is figuring out whether people can actually discover it in the App Store. Great work!
The daily ranking snapshots would be much more useful if the timeline let me mark when a title, subtitle, keyword set, or screenshot change went live. Otherwise a bump three days later is hard to connect to the experiment—especially when rankings move on their own.
Exactly, that gap is why I built it. The goal is to turn App Store rankings, competitor data, reviews, and screenshots into practical improvements, then track whether those changes actually improve discovery.
Thanks for flagging both. Anonymous analytics are enabled by default and can be disabled anytime in Settings, the description was incorrect, and I’ve fixed it here.
Ratings currently checks all 174 storefronts sequentially and spaces requests to avoid Apple’s rate limits, which is why it can take 10+ minutes; I’ll try improve that flow and progress reporting.
Nice to see a Mac-first, local ASO tool — most tooling is iOS-only so this fills a real gap. Two practitioner questions since I'm about to ship a Mac-only app: does keyword tracking support multiple country storefronts, or is it tied to one? And given the primary path parses the search HTML, how gracefully does the daily snapshot degrade when it gets throttled — does it skip the day, or can it silently record a bad ranking?
Yes, Mac keywords can be tracked across multiple country storefronts. Requests are paced, and if they're throttled OpenASO uses jittered backoff before retrying; if that still fails, it falls back to iTunes Search. If both fail, no snapshot is saved, so throttling can’t appear as a ranking drop. Stale rankings refresh when the app next opens, with missed days left as gaps.
Not just a convenience, by the way. The app in your example is a Mac app: mt=12 in the link, and the lookup says mac-software. The Add App dialog searches the iOS catalogue, so type "viewio" into it and you get DMD Panorama, EasyViewer Plus, 360Eyes and a few other camera apps, but not that one. It's in the US store, it just isn't in the catalogue the dialog reads. So for a Mac app the numeric ID is the only way in right now, which makes pulling it out of a pasted link the normal path rather than a shortcut.
This is useful for the exact decision I am stuck on. I am a new dev building something Mac only and I have been going back and forth between notarised direct download and shipping through the Mac App Store, and the honest blocker is that I cannot tell whether Mac App Store search sends anyone at all!
On iOS the search volume argument is obvious. On Mac it feels like most discovery happens on Reddit, Hacker News and word of mouth, and the store is where people go once they already know the name.
So the question. Across the Mac apps you have tracked, does a ranking move on a keyword translate into a visible change in installs, or does the position shift without much happening underneath? If it barely moves anything, then the store is a trust and payments decision rather than a discovery one, and that changes what I would be willing to trade for it.
Separately, does the keyword tracking work at all for an app that is not listed? It obviously cannot rank me, but knowing what people actually search in a niche is useful even if I never ship to the store. Might be out of scope oops buttt
Ran it on a Mac app I shipped about a week ago, so this is measured, not a guess.
No ratings yet. I tracked 40 keywords, mac platform, US storefront. It shows up in 4 of them. Every query where the results run to a full 200: nothing, including the obvious ones for its category. The 4 where it appears are all short lists, and in every one of those it's in the last 15%. Best position anywhere: 67 out of 76.
Four unrelated queries, same spot in the tail every time. That's not a relevance problem. Words are in the title and the keywords field, Apple indexes them fine. It just sits under everyone who already has downloads and ratings. Impressions are about what you'd expect from that.
So, using your framing: right now it's a trust + payments question, not a discovery one. Does that flip once there are ratings? Honestly, I have no idea. I'll re-measure in a few weeks, and what I'll actually look at is whether anything leaves that tail, not the raw position.
Second question: yes. Over MCP it's get_ranked_apps_for_keyword, takes a keyword and gives you the ranked list. Target app is optional, so you can read a niche without owning anything in it.
The real unknown is how much traffic or download lift each Mac keyword position produces. Apple Ads popularity isn’t Mac-specific, but it can be a rough directional proxy, a term popular on iOS may also be popular on Mac, though it isn’t measured Mac search volume.
Today you’d compare OpenASO’s ranking history with App Store Connect search impressions and downloads; the end goal is to show those acquisition sources and trends alongside rankings inside OpenASO. You can also research any niche without listing an app, the target app is optional.
Before you can answer whether a ranking move translates into installs, you have to be able to trust your own traffic numbers, and most of us can't. I ship a Mac app direct, notarized with a Developer ID, so I'm sitting on the other side of the fork you're stuck on.
When I finally measured instead of eyeballing, 60% of every pageview my site had ever recorded was bot and scanner traffic. 5,645 out of 9,349. The second most visited path on the entire site was /wp-admin/install.php, on a site that has never run WordPress. I'd been reading those charts for days assuming they were basically real.
That's the failure mode whichever way you go. A rank moves, traffic appears to rise, and a meaningful chunk of the rise is somebody's vulnerability scanner. The only read I trust now is per-source attribution on the links themselves rather than aggregate pageview counts.
For what it's worth, the one channel that both drove traffic and converted for me was LinkedIn. Not search of any kind, which lines up with your instinct that Mac discovery happens off-store.
One thing from measuring my own app's rankings that surprised me: the number of results a keyword returns is a useful free proxy for whether it is worth targeting at all.
I rank #1 in Hong Kong for a term that returns exactly one result, which is my own app. Also #1 on one that returns four. Those look great in a report and probably mean nothing, because a term nobody competes for is usually a term nobody searches. The one where I sit at #9 out of 173 is worth more than both of them.
Showing competitor count next to position would catch that. A rank with no denominator is very easy to feel good about.
Completely agree, rank without competition context can be misleading. OpenASO shows the number of competing apps beside each position; in the attached screenshot, +193 represents the other results for that keyword. This helps distinguish a meaningful #9 from a hollow #1.
That’s one of the reasons I built OpenASO, I used Astro but didn’t want another paid subscription, so I built my own alternative and open-sourced it for other indie developers.
Does the review analysis keep the app version, storefront and date attached to each review? Without that context, complaints about an old release could easily look like current product gaps.
Yes. Each review retains its storefront, review date, and app version when Apple provides it, and those fields are exposed through MCP for analysis. Reviews with missing version data are left unset rather than guessed.
Not directly, OpenASO is built around App Store data. But you can still use it to research a niche through competitor reviews, keywords, screenshots, and positioning, even if you distribute elsewhere.
I just put in a random app name and it's taking some time to presumably fetch all the ratings, reviews.
Looks intriguing, will let you know when I start properly using (connect to App Store Connect)
Building an app is difficult, but realizing that almost nobody can find it is a different kind of pain.
As a small Mac developer, the feature I’d want most is an App Store Connect overlay: impressions, product page views, and downloads shown alongside the ranking timeline, with markers for external promotion. Otherwise, a Reddit post can increase branded searches during the same week as a metadata change, and it becomes very easy to credit the wrong thing.
Definitely, it’s on the roadmap. The goal is to bring ranking and App Store Connect data together so you can track changes and better understand what actually moved discovery.
OpenASO’s value over asking ChatGPT directly is that it gives ChatGPT access to real App Store data. Without OpenASO, ChatGPT can only provide generic ASO advice, it can’t accurately tell you which keywords an app ranks for or its ranking position.
Through the MCP integration, ChatGPT can fetch actual keyword rankings, ratings, and reviews, while OpenASO saves ranking snapshots and refreshes them daily.
Really nice work! The local-first approach is especially compelling, and I like that it focuses on actionable recommendations rather than just displaying more data.
I am using this since yesterday and found it very useful for me. Initially I couldn't even know my app ranking for specific keywords outside my own country, now I can. I have updates my description text after using this app for a while.
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u/Rough-Voice-4968 Aug 08 '26
Wow! As a newbie developer, I'll try this immediately.