Open Source Keyword Research Tool
Keyword research carries an awkward constraint: the real search-volume numbers live behind paid APIs that no open project can legally redistribute, which is why this space stays thin. So the open tools here do not pretend to sell you metrics. They help you generate, cluster, and expand keyword ideas, or pull demand data through an API key you supply and pay for yourself, leaving the expensive numbers to whichever provider you choose. What open source does buy you is transparency and ownership: the scoring formulas are visible instead of a black box, and your keyword lists, clusters, and research history stay in your own database rather than a vendor account you rent by the seat.
OpenSEO
Open source SEO platform for keyword research, backlinks, rank tracking, site audits, and AI visibility
SerpBear
Open source search engine position tracking and keyword research app with email alerts and a built-in API
RespectASO
Privacy-first ASO keyword research for macOS with no API keys, accounts, or data leaving your machine
SEO Panel
Open source SEO control panel for managing multiple websites, with rank tracking, auditing, and backlink checks
Our picks
Pick first by surface, App Store or web, then by whether you also need rank tracking built in.
Private App Store keyword research: RespectASO RespectASO is a privacy-first ASO tool for iOS developers who want App Store keyword research without accounts, API keys, or data leaving their machine. It uses the public iTunes Search API to compute keyword popularity, difficulty, competitor breakdowns, and download estimates, all in a local SQLite database with no telemetry. It ships as a native Mac app and a Docker Compose web edition, under the AGPL. Choose it when your keywords are sensitive competitive intelligence and the analysis should stay entirely local.
Self-hostable web SEO suite: OpenSEO OpenSEO is a broader web SEO platform for teams that want a less bloated, self-hostable suite they can fork and extend. It covers keyword research with demand estimates, desktop and mobile rank tracking with SERP feature detection, backlinks, site audits, and AI visibility, and exposes an MCP server so Codex, Claude Code, and Claude Desktop can drive keyword and SERP tasks directly. It self-hosts with Docker Compose or a Cloudflare Worker under the MIT license and uses a DataForSEO key you supply for paid data, with a managed option if you prefer.
Rank tracking with keyword research: SerpBear SerpBear is the rank-tracking specialist here, monitoring unlimited domains and keywords in Google with daily, weekly, or monthly email alerts. It adds keyword research through a Google Ads test account and pulls visits, impressions, and keyword ideas from Google Search Console, all behind a built-in API. It self-hosts with Docker or runs free on Fly.io, under the MIT license. Choose it when tracking a known keyword set matters as much as finding new ones.
Where the numbers come from, and other things to check
Data provenance decides everything here, because a keyword tool is only as trustworthy as the source behind its numbers. The tools here also split by search surface, which is the first fork in the road: RespectASO does App Store keyword research for iOS developers, while OpenSEO, SerpBear, and SEO Panel all target web search. RespectASO pulls from the public iTunes Search API and computes popularity scores, difficulty, competitor breakdowns, and download estimates on your own machine. OpenSEO is a web SEO platform covering keyword research, rank tracking, backlinks, and site audits, but expects you to bring your own DataForSEO API key for paid demand data. Decide whether you are optimizing an app listing or web pages before anything else.
Whichever surface you work on, look closely at how scores are produced and where the data ages. Because the code is open, difficulty and popularity formulas are inspectable rather than a marketing label, but the assumptions still have to match your market. RespectASO keeps its data in a local SQLite database with no telemetry or accounts, so nothing leaves your Mac, which is a real advantage when the queries themselves are sensitive competitive intelligence. OpenSEO caches AI brand-visibility lookups for a day and meters API cost by usage, so confirm how fresh a number is and what each refresh costs before trusting it for planning.
Finally, weigh how each fits your actual workflow, and be realistic that even these four tools do not add up to a full open replacement for a paid suite. A solo iOS developer may only need RespectASO's local analysis and CSV; an SEO team will want OpenSEO's saved projects, rank tracking, and its MCP server for driving keyword and SERP tasks from an editor; and SerpBear offers a lighter path if the job is mostly tracking a known keyword set and pulling ideas from Google Search Console. Favor whichever makes exit easy through clean exports, since scoring state trapped in a UI is as much lock-in as any vendor cloud.
Related categories
Frequently asked questions
Are open source keyword tools as accurate as paid SEO suites?+
Accuracy depends on the data source, not the license. Paid suites blend clickstream panels, ad estimates, and proprietary SERP databases, while an open tool relies on whatever you connect it to. OpenSEO, for example, is only as good as the DataForSEO key you bring, and RespectASO is bounded by what the public iTunes Search API exposes. Treat volume and difficulty as directional, and validate important terms against your own search console, store analytics, or ad data before spending on them.
Where does the volume data actually come from?+
In open tools it comes from whatever source you wire in, and each has a bias worth knowing. OpenSEO pulls paid demand and SERP data through your own DataForSEO API key, SerpBear can research keywords via a Google Ads test account and Search Console, and RespectASO derives popularity and difficulty from the public iTunes Search API, computed locally. None of these invents a proprietary index, so record the source and collection date with each metric to tell a stale guess from usable evidence.
Do these cover App Store keywords or web SEO?+
They split by surface, which matters when choosing. RespectASO is the App Store option, an ASO tool for iOS developers that scores keyword popularity and difficulty and estimates downloads for app listings. The web side has three: OpenSEO for research, rank tracking, backlinks, and audits, SerpBear for position tracking with keyword research, and SEO Panel as an older SEO control panel with a keyword position checker. Ranking an app points to RespectASO; ranking a website points to the web tools.
What should I check before trusting a difficulty score?+
Find out which signals feed it and whether it can be recalculated. Some models weigh ranking-domain strength, backlinks, or SERP composition; others are simple proxies based on volume or competing-page counts. Open code helps here because the formula is visible rather than a label - OpenSEO and RespectASO both expose their scoring for inspection. Test any score against keywords where you already know the ranking landscape before you rely on it to prioritize work.
Can one of these replace rank tracking as well?+
Sometimes, and here the list actually leans that way. OpenSEO includes desktop and mobile rank tracking with SERP feature detection alongside its research tools, and SerpBear is a dedicated position tracker with keyword research and Google Search Console built in, so a small team can consolidate both jobs. Either way you add storage for historical positions and lean on an API quota for repeated checks. If rankings are business-critical, confirm the cadence, accuracy, and any alerting before you rely on it.
Are the API keys and stored data a security concern?+
They can be, because a keyword tool often holds credentials for paid data providers and competitive query history. OpenSEO stores a DataForSEO key you must protect, so keep it scoped and rotatable. RespectASO takes the opposite approach: no API keys, no accounts, and no telemetry, with data kept in a local SQLite database that never leaves your machine, which removes the credential risk entirely for App Store work. Match the model to how sensitive your research is.
Is self-hosting one of these worth the effort?+
Self-hosting fits when you want control over API keys, research history, and access, and every tool here supports it. RespectASO runs locally as a Mac app or a Docker Compose web edition, and OpenSEO self-hosts with Docker Compose or a Cloudflare Worker, with a managed option if you would rather not. You inherit backups, updates, and provider rate limits in return. For occasional keyword pulls the overhead may not pay off; for ongoing team work it usually does.