Absolutely! I’ve been playing around with a few tools that stay true to the open‑source spirit while really boosting SEO. First, there’s **Screaming Frog SEO Spider** – it’s open‑source, community‑driven, and great for crawling sites and spotting issues fast. Then there’s **Piwik PRO** (the open‑source version of Matomo) for analytics; it’s privacy‑friendly and lets you dig into search performance without giving up control. For automated content optimization, **RankMath** and **Yoast SEO** plugins are open‑source, and the community keeps adding new features for schema, sitemaps, and keyword tracking. All of these let you tweak performance, run tests, and keep the codebase under community scrutiny, so you get the best of both worlds. Let me know if you want to dig deeper into any of them!

Let’s dive into the crawler side first—I’ve got a feeling Scrapy will let us build a lightweight, community‑friendly engine that can still keep up with performance. We can tweak it to grab structured data, detect broken links, and feed the results straight into Matomo for analytics. Sound good?

Here’s a minimal skeleton you can copy straight into a new repo. **Folder layout** ``` scrapy-seo/ ├── scrapy_seo/ │ ├── __init__.py │ ├── items.py │ ├── middlewares.py │ ├── pipelines.py │ ├── settings.py │ └── spiders/ │ ├── __init__.py │ └── seo_spider.py ├── run_spider.py └── requirements.txt ``` **requirements.txt** ``` Scrapy celery requests ``` **scrapy_seo/items.py** ``` import scrapy class SeoItem(scrapy.Item): url = scrapy.Field() status = scrapy.Field() json_ld = scrapy.Field() rdfa = scrapy.Field() microdata = scrapy.Field() ``` **scrapy_seo/middlewares.py** ``` from bs4 import BeautifulSoup class JsonLdMiddleware: def process_response(self, request, response, spider): soup = BeautifulSoup(response.text, 'html.parser') ld_json = soup.find_all('script', type='application/ld+json') response.meta['json_ld'] = [script.string for script in ld_json] return response class RdfaMiddleware: def process_response(self, request, response, spider): # Simple extraction using BeautifulSoup; replace with rdflib if needed soup = BeautifulSoup(response.text, 'html.parser') rdfa = soup.find_all(attrs={'typeof': True}) response.meta['rdfa'] = [tag.get('typeof') for tag in rdfa] return response class MicrodataMiddleware: def process_response(self, request, response, spider): soup = BeautifulSoup(response.text, 'html.parser') micro = soup.find_all(attrs={'itemtype': True}) response.meta['microdata'] = [tag.get('itemtype') for tag in micro] return response ``` **scrapy_seo/pipelines.py** ``` import requests class StatusPipeline: def process_item(self, item, spider): item['status'] = item.get('status') or 200 return item class MatomoPipeline: def __init__(self, url, token): self.url = url self.token = token @classmethod def from_crawler(cls, crawler): return cls( url=crawler.settings.get('MATOMO_URL'), token=crawler.settings.get('MATOMO_TOKEN') ) def process_item(self, item, spider): payload = { 'idsite': 1, 'rec': 1, 'url': item['url'], 'ua': 'Scrapy', 'action_name': 'Crawl', 'token_auth': self.token, 'send': 1 } requests.post(self.url, data=payload) return item ``` **scrapy_seo/settings.py** ``` BOT_NAME = 'scrapy_seo' SPIDER_MODULES = ['scrapy_seo.spiders'] NEWSPIDER_MODULE = 'scrapy_seo.spiders' ROBOTSTXT_OBEY = True DOWNLOAD_DELAY = 1 ITEM_PIPELINES = { 'scrapy_seo.pipelines.StatusPipeline': 300, 'scrapy_seo.pipelines.MatomoPipeline': 400, } DOWNLOADER_MIDDLEWARES = { 'scrapy_seo.middlewares.JsonLdMiddleware': 543, 'scrapy_seo.middlewares.RdfaMiddleware': 544, 'scrapy_seo.middlewares.MicrodataMiddleware': 545, } MATOMO_URL = 'https://your-matomo-instance.com/matomo.php' MATOMO_TOKEN = 'your_api_token' ``` **scrapy_seo/spiders/seo_spider.py** ``` import scrapy from ..items import SeoItem class SeoSpider(scrapy.Spider): name = 'seo' allowed_domains = ['example.com'] start_urls = ['https://www.example.com'] def parse(self, response): item = SeoItem() item['url'] = response.url item['status'] = response.status item['json_ld'] = response.meta.get('json_ld', []) item['rdfa'] = response.meta.get('rdfa', []) item['microdata'] = response.meta.get('microdata', []) yield item for link in response.css('a::attr(href)').getall(): if link.startswith('http'): yield response.follow(link, callback=self.parse) ``` **run_spider.py** ``` from scrapy.crawler import CrawlerProcess from scrapy.utils.project import get_project_settings process = CrawlerProcess(get_project_settings()) process.crawl('seo') process.start() ``` That gives you a functional, lightweight crawler that pulls structured data, logs status codes, and reports each page back to Matomo in real time. You can hook Celery into the run_spider.py to schedule daily runs, and tweak DOWNLOAD_DELAY or CONCURRENT_REQUESTS_PER_DOMAIN to stay polite. Happy hacking!