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SEO Keyword Clustering Tool
What it is
SEO Keyword Clustering Tool is a free Python and Streamlit desktop application for analyzing and organizing SEO keywords. Its SERP clustering groups terms when search-result URLs overlap, using Default, Strict, or Balanced Strict algorithms with Search Volume or CPC strategies. Through the DataForSEO API, it retrieves search results, search volume, CPC, keyword difficulty, and search intent. A local SQLite cache checks stored responses before making new calls, and you can configure how long responses remain cached. The interactive workbench supports cluster analysis, filtering, and summaries, with reports exportable as multi-sheet Excel files. The README describes local embedding-based semantic clustering as unlimited and without API costs, while the roadmap also lists semantic clustering as planned. You can run the tool locally on Windows, macOS, or Linux with Python and Streamlit. It connects to DataForSEO Sandbox and Live environments, is MIT-licensed, and welcomes GitHub contributions. SERP clustering costs $0.50+ per keyword, so keyword volume depends on API costs.
For and against
For
- Groups terms by overlapping SERP URLs
- Offers three SERP clustering algorithms
- Fetches volume, CPC, difficulty, and intent
- Caches API responses locally
- Exports reports as multi-sheet Excel
Against
- SERP clustering costs $0.50+ per keyword
- Keyword volume depends on API costs
- Secure multi-user authentication is still planned
- Requires local Python and Streamlit setup
The verdict
This tool combines SERP metrics, clustering controls, caching, and spreadsheet export in a free local project. Budget for DataForSEO charges when using SERP clustering and review the roadmap for unfinished features.
Who it suits
It suits SEO practitioners who need SERP-based grouping, semantic organization, or exported cluster reports. Large keyword lists may fit the described semantic approach, while precise SERP targeting uses SERP clustering.
On the record
- Analysis and export
- The interactive workbench supports analysis, filtering, and summaries, and exports reports to multi-sheet Excel files.github.com · read 30 Sep 2026
- API cost limit
- The README lists SERP clustering API costs as $0.50+ per keyword and says the number of keywords is limited by API costs.github.com · read 30 Sep 2026
- Caching
- A local SQLite cache stores API responses and checks for cached data before making API calls; users can configure cache duration.github.com · read 30 Sep 2026
- Cost limit
- The README says SERP clustering incurs API costs of $0.50+ per keyword and that its keyword limit depends on API costs.github.com · read 30 Sep 2026
- Development status
- The roadmap lists additional languages and locations, a login system, performance improvements, and documentation work as future features.github.com · read 30 Sep 2026
- Installation
- The maker provides local installation instructions for Windows, macOS, and Linux using Python and Streamlit.github.com · read 30 Sep 2026
- Integration
- The tool connects to DataForSEO, with configuration for its Sandbox and Live API environments.github.com · read 30 Sep 2026
- Intended users
- The README says semantic clustering is best for large lists and semantic grouping, while SERP clustering is best for precise SERP targeting.github.com · read 30 Sep 2026
- Keyword metrics
- The tool fetches SERP results, search volume, CPC, keyword difficulty, and search intent through the DataForSEO API.github.com · read 30 Sep 2026
- License and contributions
- The project says it is MIT-licensed and welcomes contributions through GitHub issues and pull requests.github.com · read 30 Sep 2026
- Maker
- The GitHub profile identifies the maker as Fassih Fayyaz and lists Multan, Pakistan.github.com · read 30 Sep 2026
- Purpose
- It is a Python desktop tool for SEO keyword analysis and organization using SERP clustering and local semantic clustering.github.com · read 30 Sep 2026
- Security and trust
- The README instructs users to store DataForSEO credentials in a local .streamlit/secrets.toml file and states that the project is licensed under MIT.github.com · read 30 Sep 2026
- Security status
- The roadmap lists adding a secure authentication system for multiple users as a future feature.github.com · read 30 Sep 2026
- Semantic clustering
- Its semantic clustering uses embedding models, runs locally, and is described as free of API costs with unlimited keywords.github.com · read 30 Sep 2026
- SERP clustering
- It groups keywords based on overlapping SERP URLs and offers Default, Strict, and Balanced Strict algorithms with Search Volume or CPC strategies.github.com · read 30 Sep 2026
- SERP data
- The tool fetches SERP results, search volume, CPC, keyword difficulty, and search intent through the DataForSEO API.github.com · read 30 Sep 2026
