RSS & Atom Feed Monitor - New Items Only + AI Digest
Under maintenancePricing
from $0.80 / 1,000 feed item delivereds
RSS & Atom Feed Monitor - New Items Only + AI Digest
Under maintenanceMonitor any number of RSS 2.0, Atom and RSS 1.0 (RDF) feeds and get only the items you have not seen yet. Keyword filters, conditional GET, Shift_JIS/EUC-JP safe, optional Claude summaries and digest with your own Anthropic API key.
Pricing
from $0.80 / 1,000 feed item delivereds
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Koban Tools
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2 days ago
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Monitor any number of RSS 2.0, Atom and RSS 1.0 (RDF) feeds and get only the items you have not seen before. Put it on an Apify Schedule (hourly, daily...) and every run delivers just the fresh entries - ready for Slack, email, Google Sheets, Make, n8n, Zapier or your AI agent via MCP.
Optional: let Claude write a 1-2 sentence summary per item and/or one Markdown digest per run, using your own Anthropic API key.
Why this feed monitor
- New items only, across runs. Seen item IDs are remembered per feed in a key-value store in your account. No duplicates in your downstream tools.
- Polite and cheap. Uses HTTP conditional requests (
ETag/If-Modified-Since). Unchanged feeds return304 Not Modifiedand cost almost nothing. - Handles real-world feeds. RSS 2.0, Atom, RSS 1.0/RDF,
content:encoded, Dublin Core dates, enclosures (podcasts), HTML stripped to clean text. Correctly decodes Shift_JIS and EUC-JP feeds that break many parsers (common on Japanese sites), and timezone-less Japanese dates. - Keyword filters (include / exclude, case-insensitive, works with Japanese and Chinese text) and an age filter.
- Budget-safe. Respects your "Maximum cost per run". If the limit is hit, undelivered items stay pending and arrive on the next run - nothing is silently lost.
- AI optional, bring your own key. Model usage is billed by Anthropic directly to you. Default model
claude-haiku-4-5(cheapest); you can choose any Claude model.
Use cases
- Competitor blogs, changelogs and release notes -> Slack channel
- Security advisories (vendor and government feeds) -> ticket queue
- News monitoring for a brand or topic with keyword filters -> daily AI digest by email
- Podcast feed watcher (enclosure URLs) -> transcription pipeline
- Japanese government / corporate press-release feeds -> English digest (set Summary language to English)
Input
| Field | Description |
|---|---|
feedUrls | List of feed URLs (required). |
onlyNewItems | Remember delivered items and output only unseen ones (default true). |
firstRunBehavior | emit-all (default) outputs current items on the first run; baseline-only just remembers them. |
stateStoreName | Key-value store that holds the memory. Use different names for independent monitors. |
maxItemsPerFeed | Max items per feed per run (default 50). Older items beyond this limit in the same feed snapshot are marked as seen. |
publishedWithinDays | Skip items older than N days. |
includeKeywords / excludeKeywords | Keyword filters on title, summary and categories. |
includeContentHtml | Also output full HTML content when available. |
aiMode | none, per-item, digest, or both. |
anthropicApiKey | Your Anthropic API key (secret input, needed only for AI). |
aiModel, aiLanguage, aiInstructions | Model ID, output language, extra instructions. |
Example:
{"feedUrls": ["https://hnrss.org/frontpage", "https://github.blog/feed/"],"onlyNewItems": true,"includeKeywords": ["security", "pricing"],"aiMode": "digest","anthropicApiKey": "sk-ant-...","aiLanguage": "English"}
Output
One dataset item per delivered feed entry:
{"feedUrl": "https://github.blog/feed/","feedTitle": "The GitHub Blog","feedFormat": "rss2","itemId": "https://github.blog/?p=99381","title": "Hack the World: Why hackathons are still the best place to learn to build","link": "https://github.blog/developer-skills/career-growth/hack-the-world-...","publishedAt": "2026-10-09T16:00:00.000Z","author": "Ed Summers","categories": ["Career growth", "Developer skills"],"summary": "The barriers to building software have collapsed. ...","aiSummary": null,"enclosures": [],"isNew": true,"detectedAt": "2026-10-12T12:58:11.580Z"}
The run's key-value store also contains:
RUN_REPORT- per-feed status (ok,not-modified,error), item counts and detected encoding.DIGEST.md- the AI digest (whenaiModeisdigestorboth).
Pricing (pay per event)
You pay only for results:
| Event | Price |
|---|---|
| Feed item delivered | $0.0008 per item ($0.80 per 1,000) |
| AI item summary | $0.002 per item (+ your own Anthropic usage) |
| AI digest | $0.01 per digest (+ your own Anthropic usage) |
A run where nothing changed (all feeds 304 Not Modified) delivers no items, so you pay only the small Apify start fee.
Scheduling
Create an Apify Schedule (e.g. every hour) with the same input. Because the memory is stored in your account, each run only returns what is new since the previous run. Connect an integration (Slack, email, webhook, Google Sheets) to the "run succeeded" event to push new items automatically.
Responsible use
This Actor only reads feeds you list. Feeds are published for automated reading, but some publishers limit how their content may be reused - make sure your use of the content complies with each publisher's terms. The Actor sends a descriptive User-Agent, uses conditional requests, and fetches each feed once per run with low concurrency. It does not bypass logins, paywalls or bot protection.
FAQ
Does it scrape article pages? No. It reads only the feed itself. If the feed contains full content, enable includeContentHtml.
Where is my Anthropic key stored? It is a secret input: Apify stores it encrypted and it is only used to call the Anthropic API during your run.
A feed returns an error. Check RUN_REPORT for the HTTP status. Other feeds in the same run are still processed.
Japanese feed shows garbled text in other tools. This Actor detects the charset from the HTTP header and the XML declaration (Shift_JIS, EUC-JP, UTF-8 and others) and always outputs UTF-8.
About
Developed and maintained by koban-tools, with AI-assisted development (Claude). The code is tested against real RSS, Atom and RDF feeds before each release. Questions and bug reports are welcome via the Issues tab (English or Japanese).