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Free, open-source ASO keyword research tool — self-hosted via Docker. No API keys, no accounts, no data leaves your machine.

379 starsHTML

RespectASO – Free, open-source, self-hosted ASO keyword research tool

by cesncn·Feb 23, 2026·1 point·0 comments
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AI Analysis

●●SolidSolve My ProblemCozy

Free ASO without third-party servers beats paid tools, but iTunes API signals are noisy baselines.

Strengths
  • •Privacy-first: zero telemetry, runs entirely locally via Docker, no vendor lock-in.
  • •6-signal popularity model + 7-factor difficulty scoring is thoughtful feature parity with commercial tools.
  • •Low friction: single Docker command, no onboarding, targets a real pain point (ASO tool costs).
Weaknesses
  • •Relies solely on public iTunes API—signals are indirect proxies, less accurate than proprietary ranking data.
  • •No user traction or validation shown; ASO tool market has incumbents (App Annie, mobile.dev) with richer data.
Category
Productivity
Target Audience

iOS app developers, indie app publishers, ASO consultants needing privacy-first keyword research

Similar To

App Annie (Adjust) · Sensor Tower · Mobile Action

Post Description

I built a free, open-source ASO keyword research tool that runs locally via Docker. You don't need any API keys or accounts; and no data leaves your machine.

WHY FREE & WHY OPEN-SOURCE? What any ASO tool gives you are just algorithmically estimations. I have tried many and I can say they are not consistent at all. And they likely over-complicate things in their solutions where over-complication does not necessarily create a better solution.

WHY SELF-HOSTED? I wanted to provide this as free. If I hosted the whole thing at a site, I suspect that abuse would be one of the things I would need to deal with, and it would also come with lots of infrastructure costs. And users would share their data suspecting how the hack this is possible for free of charge. Hosting locally is extremely easy, can be done in less than 2 minutes.

HOW IT WORKS IN A NUTSHELL? It uses the public iTunes Search API to estimate keyword popularity (6-signal model), difficulty (7 weighted factors), and downloads per ranking position. You can scan 30 App Store countries, track your app's rank, and export to CSV. It has all the core functions one can ask for.

Installation: git clone https://github.com/respectlytics/respectaso.git cd respectaso docker compose up -d

License: AGPL-3.0. Built with Django + SQLite + Tailwind.

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