xseo 0.2.0

Local-first desktop SEO crawler

xseo

A local-first desktop SEO crawler. Audit your site on your own machine — no cloud, no accounts, no data leaves your computer.

xseo is a desktop application that crawls a website, extracts on-page SEO signals, detects common issues and content duplication, and renders the results in a clean UI. Everything runs locally and persists to a single SQLite file under ~/.xseo/.

Features

• Live crawling with a real-time progress view and a threaded background worker that keeps the UI responsive.
• Polite by default — respects robots.txt and applies a configurable per-request delay so you don't hammer the sites you audit.
• On-page extraction of titles, meta descriptions, headings, canonicals, robots directives, internal/external links, and more via selectolax.
• Issue detection for missing/duplicate titles and descriptions, thin content, heading problems, broken links, and other common SEO defects.
• Duplicate content detection through content hashing and grouped read models.
• Sortable result tables for pages, issues, and duplicate groups, with a double-click page detail dialog.
• CSV export for every result view, so you can pipe findings into spreadsheets or other tools.
• Local persistence in SQLite at ~/.xseo/xseo.sqlite3. The last crawl is restored automatically on launch.
• Clean architecture — domain, application, and adapter layers are strictly separated, with ports/adapters for HTTP, persistence, export, and the UI.

Screenshots

Configure a crawl, then watch progress stream in live:

Control	Progress

Review crawled pages, detected issues, and duplicate content groups:

Pages	Duplicates

Double-click any page for full detail — headings, links, redirects, and per-page issues:

Tech stack

• Python 3.12+
• PySide6 for the desktop UI
• httpx for HTTP fetching
• selectolax for fast HTML parsing
• SQLite for local storage
• pytest, hypothesis, and pytest-qt for unit, property-based, and UI tests

Install

Download a ready-to-run build (no Python needed)

Grab the latest .zip for your OS from the Releases page, unzip it, and run the xseo executable inside.

The builds are not code-signed yet, so the OS may warn you the first time:

• macOS: right-click the app → Open → Open (or System Settings → Privacy & Security → Open Anyway).
• Windows: on the SmartScreen prompt, click More info → Run anyway.

Install from PyPI (for Python users)

pipx install xseo   # isolated, recommended
# or
pip install xseo

Then launch with xseo-ui. Requires Python 3.12 or newer.

From source

python3 -m pip install -e '.[test]'

Run

Launch the desktop UI:

xseo-ui

Or from the source tree:

python3 -m xseo.ui.app

Enter a URL, click Start Crawl, and watch the progress tab fill in. When the crawl finishes, browse pages, issues, and duplicate groups in their respective tabs. Double-click any page row for full detail, or export any view to CSV.

Verify

python3 -m compileall src tests
python3 -m pytest -q

The current suite has 145 tests covering domain logic, adapters, integration, property-based invariants, and UI smoke tests.

Project layout

src/xseo/
├── domain/         # entities, value objects, ports, validation, events
│   ├── crawler/    # frontier + crawl engine
│   ├── extraction/ # HTML extraction
│   ├── analysis/   # SEO issue detection
│   └── duplicates/ # content duplicate detection
├── application/    # services, commands, queries, read models
├── adapters/       # HTTP, persistence, export, background worker, event bridge
└── ui/             # PySide6 app, widgets, controller

Contributing

Contributions are welcome — see CONTRIBUTING.md for dev setup, how to run the checks (ruff + pytest), and the project conventions.

About

I built xseo because I needed it. I was starting a new project and wanted a fast way to scan it for SEO issues without uploading URLs to a third-party tool, paying for another subscription, or fighting a heavy web dashboard. I wanted something that ran on my desktop, was honest about what it found, and stored results in a file I owned — so I wrote it, and I'm sharing it in case it's useful to anyone else who wants a small, local, hackable SEO crawler.

This is an early prototype. It works end-to-end and I use it on my own projects, but expect rough edges. Issues and PRs are welcome.

Built by Yuri Silva — @yurisilvapi on X/Twitter.