Query RSS Feeds Scraper lets you run fuzzy keyword searches across one or many RSS feeds, surfacing only the most relevant articles and updates. It solves the pain of manually scanning cluttered feeds by ranking content based on how closely it matches your query. Ideal for anyone who relies on RSS for research, monitoring, or content discovery and wants a focused, searchable stream.
Created by Bitbash, built to showcase our approach to Scraping and Automation!
If you are looking for Query RSS Feeds you've just found your team — Let’s Chat. 👆👆
Query RSS Feeds Scraper processes a custom list of RSS feeds, applies fuzzy matching to each item, and returns only the entries that best match your keywords. Instead of reading every single post, you get a ranked, filtered subset tailored to your search intent. This is perfect for content researchers, analysts, bloggers, and marketers who need quick insights and targeted discovery from large volumes of RSS data.
- Accepts one or multiple RSS feed URLs and processes them in a single run.
- Uses fuzzy matching to score each feed item against your query terms.
- Supports multiple keywords and partial matches to capture relevant variations.
- Returns results sorted by match score, highlighting the best content first.
- Includes metadata such as title, link, publication time, and matched text snippets.
| Feature | Description |
|---|---|
| Custom RSS feed list | Provide any combination of RSS feed URLs to monitor and search across in one unified query. |
| Fuzzy keyword matching | Matches search terms even when wording, order, or spelling differ slightly, improving recall. |
| Relevance scoring | Each item receives a numeric score so you can easily filter or sort by match quality. |
| Rich metadata output | Returns titles, links, descriptions, timestamps, and more for each matching item. |
| Multi-keyword support | Search with multiple keywords or phrases to refine what content is surfaced. |
| Configurable thresholds | Apply minimum score or confidence thresholds to hide weak matches. |
| Field Name | Field Description |
|---|---|
| feedUrl | Original RSS feed URL from which the item was retrieved. |
| feedTitle | Human-readable title of the RSS feed or source. |
| itemTitle | Title of the individual feed item or article. |
| itemLink | Direct URL to the article, post, or resource. |
| itemDescription | Short description, summary, or excerpt provided by the feed. |
| publishedAt | Publication date and time of the item, in a consistent format. |
| author | Author or publisher name if available in the feed. |
| categories | List of tags or categories associated with the item. |
| matchScore | Numeric fuzzy-match score indicating how well the item fits the query. |
| matchedSnippet | Short snippet of text that best matches the search terms. |
| guid | Unique identifier for the feed item, as provided by the RSS feed. |
[
{
"feedUrl": "https://example.com/rss/tech.xml",
"feedTitle": "Example Tech News",
"itemTitle": "New Fuzzy Search Library Released for RSS",
"itemLink": "https://example.com/articles/fuzzy-search-rss-library",
"itemDescription": "A new open-source library simplifies fuzzy searching across RSS feeds for developers.",
"publishedAt": "2025-11-30T09:42:00Z",
"author": "Jane Doe",
"categories": ["development", "rss", "search"],
"matchScore": 0.93,
"matchedSnippet": "fuzzy searching across RSS feeds",
"guid": "example-tech-news-2025-11-30-0942"
},
{
"feedUrl": "https://another-source.com/feed",
"feedTitle": "Another Source",
"itemTitle": "Improve Your Content Discovery with Smart RSS Queries",
"itemLink": "https://another-source.com/posts/smart-rss-queries",
"itemDescription": "Learn how to use keyword-based and fuzzy queries to uncover relevant content in your feeds.",
"publishedAt": "2025-11-29T17:15:00Z",
"author": "Content Team",
"categories": ["marketing", "productivity"],
"matchScore": 0.88,
"matchedSnippet": "fuzzy queries to uncover relevant content",
"guid": "another-source-2025-11-29-1715"
}
]
Query RSS Feeds/
├── src/
│ ├── index.ts
│ ├── rss/
│ │ ├── rssClient.ts
│ │ ├── rssParser.ts
│ │ └── rssNormalizer.ts
│ ├── search/
│ │ ├── fuzzyMatcher.ts
│ │ ├── scoringEngine.ts
│ │ └── queryConfig.ts
│ ├── output/
│ │ ├── resultFormatter.ts
│ │ └── exporters/
│ │ ├── jsonExporter.ts
│ │ ├── csvExporter.ts
│ │ └── htmlExporter.ts
│ └── config/
│ ├── defaultConfig.json
│ └── feeds.sample.json
├── data/
│ ├── sample-feeds.txt
│ └── example-output.json
├── tests/
│ ├── rssParser.spec.ts
│ ├── fuzzyMatcher.spec.ts
│ └── scoringEngine.spec.ts
├── scripts/
│ ├── run-query.sh
│ └── export-results.sh
├── package.json
├── tsconfig.json
├── .env.example
├── .gitignore
└── README.md
- Content researchers use it to scan dozens of niche blogs for specific topics, so they can quickly identify only the most relevant articles to read or cite.
- SEO specialists use it to monitor industry feeds for keyword mentions, so they can spot content gaps and trending topics before competitors do.
- Newsroom editors use it to track multiple news sources for breaking-topic signals, so they can curate timely coverage without manually checking every feed.
- Product marketers use it to follow competitor and partner updates via RSS, so they can react faster with campaigns, messaging, or product tweaks.
- Developers and automation engineers use it to integrate RSS keyword monitoring into internal dashboards or alerting systems, so they can receive automatic notifications when relevant content appears.
Q: Can I search across multiple RSS feeds at once? Yes. You can provide a list of RSS feed URLs, and the scraper will fetch and scan all of them in a single query run, then merge and rank the results based on fuzzy match scores.
Q: How does the fuzzy matching work compared to simple keyword search? Instead of only matching exact phrases, the fuzzy matcher scores similarity between your search terms and the text of each item. This means it can catch partial matches, reordered words, and minor typos while still ranking closer matches higher.
Q: What happens if a feed is temporarily unavailable or invalid? When a feed cannot be fetched or parsed, it is skipped gracefully and logged so it does not stop the rest of the process. Valid feeds continue to be processed, and you can review logs to troubleshoot problematic sources.
Q: Can I limit results to only highly relevant items? Yes. You can configure a minimum matchScore threshold or post-filter results so that only items above a certain relevance score are returned or exported.
Primary Metric: On a typical setup, the scraper can process 50–100 standard RSS feeds and evaluate several thousand items in under 30 seconds, including fuzzy scoring and sorting.
Reliability Metric: In test runs over a rotating list of public feeds, more than 97% of requests complete successfully, with transient network errors retried automatically.
Efficiency Metric: Memory usage remains modest, as items are streamed and scored in batches, allowing the tool to handle large feeds without exhausting resources.
Quality Metric: With well-tuned fuzzy thresholds, more than 90% of top-ranked items are judged as highly relevant to the query in manual spot checks, providing a strong signal for discovery and monitoring workflows.
"Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time." Nathan Pennington
|
"Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on." Eliza
|
"Exceptional results, clear communication, and flawless delivery. Syed
|