SEO Keyword Clustering Tool

Overview

SEO Keyword Clustering Tool is a locally run Python and Streamlit application for organizing keyword lists around search results. It best suits SEO practitioners who want SERP-focused clustering and are comfortable configuring DataForSEO. Its strongest case is a flexible, exportable workflow; API costs and uncertainty about semantic clustering make it a less straightforward choice for large-scale or semantic-first work.

Key features

SERP clustering and keyword metrics

The tool groups terms that share URLs in search results, with Default, Strict, and Balanced Strict algorithms and Search Volume or CPC strategies. Those options give users control over how tightly to group keywords and how to prioritize them, which is useful when building campaigns around specific search results. DataForSEO supplies SERP results, search volume, CPC, keyword difficulty, and search intent. Sandbox and Live API environments can be configured, but SERP clustering costs $0.50+ per keyword according to the project, so the API bill—not simply the ability to upload a large batch—sets the practical scope of analysis.

Cache, workbench, and exports

A local SQLite cache checks for saved API responses before making new calls, and its retention duration is configurable. That can help avoid repeated requests during ongoing analysis, though it does not eliminate the cost of gathering new data. The interactive workbench supports filtering and summarizing clusters; CSV and multi-sheet Excel exports make the results usable in downstream reporting.

Semantic clustering and project status

The project describes local embedding-based semantic clustering as unlimited and free of API charges, an appealing contrast for grouping large lists by meaning. However, the README also places semantic clustering on the roadmap. Its availability is therefore unclear, so readers who require semantic grouping should not make it the deciding feature without confirming it first. The roadmap also includes multiple languages and locations, a login system, performance work, and documentation work as future features.

Pricing

The tool is free, with no paid plan described. Free software does not make SERP analysis cost-free: DataForSEO usage is quoted at $0.50+ per keyword, and the keyword limit depends on API costs. Readers should factor those usage charges into a budget before clustering large lists. The project gives no subscription renewal or seat terms; a secure multi-user authentication system remains a planned feature, so this is not a clear fit for teams needing account-based access.

Platforms

The application can be run locally on Windows, macOS, or Linux using Python and Streamlit. It is also categorized as web and self-hosted, but its installation instructions center on running it locally rather than on a hosted service. Users configure DataForSEO credentials in a local .streamlit/secrets.toml file, keeping setup tied to a machine or self-managed environment.

Who it's for

Choose it if you want precise SERP-targeted keyword groups, need search metrics alongside clustering, and can manage API credentials and per-keyword costs. Batch upload, adjustable grouping strategies, a local cache, and spreadsheet exports support a deliberate research workflow. Look elsewhere if you need confirmed semantic clustering, built-in multi-user authentication, or predictable costs for very large keyword volumes.

Pros and cons

• Pros: Three SERP algorithms and two prioritization strategies offer useful control over how keyword groups are formed.
• Pros: DataForSEO metrics, configurable local caching, an analysis workbench, and CSV or Excel exports bring research and reporting into one workflow.
• Pros: Local installation and an MIT license suit users who want to run or adapt the project themselves.
• Cons: SERP clustering carries stated API costs of $0.50+ per keyword, which can make broad analysis expensive.
• Cons: Semantic clustering is described as both a capability and a planned feature, leaving its current status uncertain.
• Cons: Multi-user authentication is still planned, limiting its appeal for teams that need secure shared access.

Alternatives

Compare keyword clustering tools if you want to weigh this local, API-dependent workflow against other options.

• 100 SEO Tools Keyword Clustering Tool is a better fit for users who want a browser-based free option with no signup, limits, or hidden costs.
• Absolute Cluster may suit users who want a web workflow with a free tier capped at one project and 1,000 keywords, plus content briefs, an internal-linking map, exports, and one article draft.
• ContentGecko Keyword Clustering is an option for users who want a web free tier for up to 200 keywords or a paid plan with monthly keyword credits.
• NeedMyLink Keyword Clustering Tool suits readers looking for a web-based free allowance of 500 keywords monthly, or 1,000 after email signup.
• Optiwing is another web-based freemium option for readers comparing credit-based monthly plans or a one-time credit package.
• Pro SERP Cluster may be preferable for a browser-based free workflow capped at 500 keywords per clustering run, with CSV import and export.
• SEO Algorithm Keyword Clustering offers a web free tier for up to 200 keywords without signup or credits, with separate SERP-based and semantic options.
• Topvisor is worth considering if you want a web, API, or extension option with unlimited projects and keywords on its free XS plan.

Verdict

SEO Keyword Clustering Tool is a sound choice for technically comfortable SEOs who prioritize precise SERP overlap, useful keyword metrics, and locally managed analysis. Its combination of adjustable clustering and exportable reports is compelling, but the $0.50+ per-keyword API cost is the central trade-off. Choose another tool if your workflow depends on confirmed semantic clustering, secure multi-user access, or a clearer cost ceiling.