SEO Keyword Clustering Tool

Overview

SEO Keyword Clustering Tool is a Python and Streamlit application for organizing SEO keyword lists, suited to SEO practitioners who want control over SERP-based grouping and are comfortable running software locally. Its adjustable clustering and exportable analysis are useful, but DataForSEO charges make large SERP jobs a cost decision rather than a free workflow.

Key features

SERP clustering and keyword metrics

The main mode groups keywords by overlap among their search-result URLs. Default, Strict, and Balanced Strict algorithms, paired with Search Volume or CPC strategies, let users shape how groups are formed and prioritized. That range is valuable for precise SERP targeting; the trade-off is reliance on DataForSEO, which supplies SERP results, search volume, CPC, keyword difficulty, and search intent.

Batch uploads support working with lists rather than one term at a time, but the project puts SERP API costs at $0.50+ per keyword and says the practical keyword limit depends on those costs. Users can configure either DataForSEO's Sandbox or Live environment. This is not a good fit for teams that need predictable bulk processing without per-keyword API expense.

Cache, analysis, and exports

A local SQLite cache checks for previous API responses before making calls, and its duration is configurable. It can avoid repeat requests for cached data, though it does not eliminate the cost of retrieving new results. The interactive workbench lets users filter and summarize clusters, then export reports as multi-sheet Excel files; CSV is also supported. That makes the tool more useful than a clustering step alone for people who want to review or share findings in familiar spreadsheet formats.

Semantic clustering

The project describes local embedding-based semantic clustering as unlimited and free of API charges, and recommends semantic grouping for large lists. However, it also labels semantic clustering a planned feature in its roadmap. Since that leaves its present availability unclear, buyers should not base a workflow on it without first confirming it can be used in their setup.

Pricing

The tool is free, with no paid plan described. That removes a software subscription but does not make SERP analysis cost-free: DataForSEO usage is priced by the project at $0.50+ per keyword, so users handling substantial lists should budget for API calls. The cache may reduce repeat calls, but new SERP data remains the meaningful operating cost. No seat or quota terms are given; the stated limit is the user's willingness to pay API costs.

Platforms

The application is described as a Python and Streamlit desktop tool, with local installation instructions for Windows, macOS, and Linux. Its platform scope also includes web and self-hosted use, but operation depends on installing and running the local Python and Streamlit application rather than choosing among separately described hosted plans.

Who it's for

This is a strong fit for independent SEO specialists and technically comfortable teams who need configurable SERP overlap clustering, keyword metrics, and spreadsheet-ready reports, and who can manage DataForSEO credentials and costs. Users seeking semantic grouping for large lists may find the local embedding approach appealing if it is usable in their version. Teams needing multi-user access should look elsewhere for now: secure authentication is a roadmap item, not a current capability.

Pros and cons

Pros: Three clustering algorithms and two prioritization strategies provide meaningful control over SERP group formation.

Pros: Search volume, CPC, difficulty, and intent accompany SERP results, while the workbench and multi-sheet Excel export support further analysis.

Pros: A configurable SQLite cache can reuse prior API responses, and the MIT license permits use and contribution.

Cons: SERP API costs of $0.50+ per keyword can make broad keyword sets expensive.

Cons: Semantic clustering's status is unclear because it is described both as a capability and as planned work.

Cons: Secure multi-user authentication remains on the roadmap, limiting its fit for teams that need managed shared access.

Alternatives

For more options, browse Keyword Clustering Tools. Choose KW Clusterized if broad platform coverage matters more than this tool's stated DataForSEO and workbench detail. RankYak Keyword Clustering Tool is a web and API alternative with a free plan capped at 50 keywords, making it a clearer starting point for small lists. SEOcluster.ai suits readers who want a web-based freemium tool with a free plan that combines clustering with briefs and content pages, within its stated monthly caps.

Seonio Keyword Clustering is another web option, with a free plan of 10 credits per month and a paid annual Starter plan. Absolute Cluster is worth considering for a free web plan that specifies up to 1,000 keywords along with briefs, a roadmap, and internal linking features. SEO Algorithm Keyword Clustering offers a no-signup free option for up to 200 keywords, while its other clustering plans use credits.

beserp Keyword Clustering may suit users who prefer non-expiring signup credits and one-time credit purchases rather than a monthly subscription. ContentGecko Keyword Clustering offers a free version capped at 200 keywords and a paid plan with 50,000 keyword credits per month. These alternatives are web-based, unlike a locally installed Python and Streamlit workflow.

Verdict

Choose SEO Keyword Clustering Tool if you want adjustable SERP-overlap grouping, detailed keyword metrics, and exportable analysis in a self-hosted workflow, and can manage DataForSEO costs yourself. Look elsewhere if you need inexpensive processing at scale, dependable semantic clustering today, or secure multi-user access.