RSS + WhatsApp: daily news digests, already summarized
Your feeds don’t have a “done” state. You open an RSS reader for a quick check, and suddenly you’re juggling 40 tabs, half-read threads, and the nagging feeling you still missed the one story that mattered. It’s noisy. And it steals attention in tiny, expensive chunks.
Marketing leads feel this before standups. Founders feel it between calls. And consultants trying to stay sharp for clients? Same problem. This RSS WhatsApp digest automation turns scattered headlines into one clean summary you can skim in a minute.
Below you’ll see exactly how the workflow pulls from multiple RSS sources, normalizes the data, summarizes with OpenAI, and sends a daily digest to WhatsApp (or anywhere else you prefer).
How This Automation Works
The full n8n workflow, from trigger to final output:
n8n Workflow Template: RSS + WhatsApp: daily news digests, already summarized
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The Problem: Daily news becomes daily distraction
Trying to “keep up with the news” sounds responsible until you do it manually. You bounce between four different feeds, each one formatted differently, and you end up reading the same story twice because two sites syndicated it. Then you copy links into a note, or you message yourself “read later” items that never get read later. Worst part is the mental overhead. You’re constantly re-deciding what matters, which is tiring before the real work even starts.
It adds up fast. Here’s where the routine usually breaks down.
- You scan dozens of headlines to find maybe five worth reading.
- Different RSS feeds label fields differently, so any “combined view” turns messy quickly.
- Sharing a quick roundup with a teammate becomes a manual copy-paste job you postpone.
- You spend about 20 minutes catching up, then still feel behind.
The Solution: A summarized daily digest delivered to WhatsApp
This workflow runs on a schedule you choose (daily is the sweet spot for most people). At each run, it pulls fresh items from four RSS feeds, then cleans up the fields so every article looks consistent: title, link, published date, and source. Next, it merges everything into one list, filters down to the most relevant or recent entries, and keeps it tight by limiting the set to the latest 10 items. Those 10 are then aggregated into one block of text that OpenAI can summarize cleanly. Finally, the workflow sends the finished digest to a WhatsApp endpoint via a webhook, which means the summary lands where you actually look, not in another “tool you should check.”
The flow starts with a schedule trigger. Then n8n fetches and standardizes RSS items from multiple sources, merges them, and selects the newest entries. OpenAI generates a readable digest, and an HTTP request delivers it to WhatsApp (or a different destination if you swap the final step).
What You Get: Automation vs. Results
| What This Workflow Automates | Results You’ll Get |
|---|---|
|
|
Example: What This Looks Like
Say you track four RSS sources and you typically spend about 5 minutes per feed to skim, open a few links, and decide what’s worth reading. That’s roughly 20 minutes a day, and honestly it’s easy for it to balloon. With this workflow, the “work” becomes almost nothing: it runs on schedule, grabs the newest 10 items total, and sends a WhatsApp digest after OpenAI summarizes it. You read one message, maybe for a minute, and move on.
What You’ll Need
- n8n instance (try n8n Cloud free)
- Self-hosting option if you prefer (Hostinger works well)
- RSS feed URLs for the sources you follow
- OpenAI account to generate the daily summaries
- WhatsApp API/webhook endpoint (get it from your WhatsApp provider)
Skill level: Intermediate. You will connect accounts, paste feed URLs, and set a webhook URL for WhatsApp delivery.
Don’t want to set this up yourself? Talk to an automation expert (free 15-minute consultation).
How It Works
A schedule kicks things off. You decide when it runs (daily, hourly, weekdays only). n8n starts the workflow automatically, so you never have to remember to “go check the news.”
RSS items are fetched and cleaned up. The workflow reads four separate RSS feeds, then maps each feed’s fields into a consistent format using Edit Fields steps. This matters more than it sounds, because RSS feeds often label content differently, and messy inputs lead to messy summaries.
The workflow selects what’s worth summarizing. Everything gets merged into one list, filtered for recency (and optionally keywords), then restricted to the 10 newest entries. Short list, less noise.
OpenAI writes the digest and WhatsApp receives it. Articles are aggregated into a single content block, summarized with the OpenAI Chat Model node, and sent out through an HTTP request to your WhatsApp webhook endpoint.
You can easily modify the RSS sources to match your niche, or change WhatsApp delivery to email or Telegram based on your needs. See the full implementation guide below for customization options.
Step-by-Step Implementation Guide
Step 1: Configure the Schedule Trigger
Set the workflow to run on a daily schedule and fan out to multiple RSS sources in parallel.
- Add the Scheduled Start node as your trigger.
- Set the schedule rule to trigger at hour
3in Scheduled Start. - Confirm that Scheduled Start outputs to Fetch RSS Source A, Fetch RSS Source B, Fetch RSS Source C, and Fetch RSS Source D in parallel.
Execution Note: Scheduled Start outputs to both Fetch RSS Source A and Fetch RSS Source B and Fetch RSS Source C and Fetch RSS Source D in parallel.
Step 2: Connect RSS Sources and Map Fields
Pull articles from four RSS feeds and normalize the fields for consistent downstream processing.
- In Fetch RSS Source A, set URL to
https://uxdesign.cc/feed. - In Fetch RSS Source B, set URL to
https://www.technologyreview.com/topic/artificial-intelligence/feed/. - In Fetch RSS Source C, set URL to
https://the-decoder.com/feed/. - In Fetch RSS Source D, set URL to
https://www.theverge.com/rss/index.xml. - In Map Feed Fields D, map title to
{{ $json.title }}, pubDate to{{ $json.pubDate }}, and conteudo to{{ $json.content }}. - In Map Feed Fields A, map title to
{{ $json.title }}, pubDate to{{ $json.pubDate }}, and conteudo to{{ $json['content:encoded'] }}. - In Map Feed Fields B, map title to
{{ $json.title }}, pubDate to{{ $json.pubDate }}, and conteudo to{{ $json.contentSnippet }}. - In Map Feed Fields C, map title to
{{ $json.title }}, pubDate to{{ $json.pubDate }}, and conteudo to{{ $json.contentSnippet }}.
Execution Note: Each feed maps into Combine Feeds from Map Feed Fields A, Map Feed Fields B, Map Feed Fields C, and Map Feed Fields D.
Step 3: Merge and Filter Recent Articles
Merge the normalized feed items, filter for recency, and limit the digest size.
- In Combine Feeds, set Number of Inputs to
4. - In Filter Recent Entries, configure the condition with Left Value
{{ $json.pubDate }}, Operationafter, and Right Value{{ $today.minus({ days: 1 }) }}. - In Restrict Items, set Max Items to
10.
⚠️ Common Pitfall: If the RSS feed pubDate formats vary, the date filter in Filter Recent Entries may exclude all items. Validate the date format in a test run.
Step 4: Aggregate Articles for Summarization
Prepare a combined dataset of titles, dates, and content for the AI summary.
- In Aggregate Articles, set Include to
specifiedFields. - Set Aggregate to
aggregateAllItemData. - Set Fields to Include to
title, pubDate, conteudo.
Step 5: Set Up AI Summarization
Generate a concise digest of the most important articles using the AI assistant.
- Open AI Summary Builder and set Resource to
assistant. - Set the Text prompt to the full expression block starting with
=I've received news articles via RSS...and including the 10 article slots such as{{ $json.data[0].title }}and{{ $json.data[0].conteudo }}. - Credential Required: Connect your
openAiApicredentials in AI Summary Builder.
⚠️ Common Pitfall: Ensure the assistant ID is configured in AI Summary Builder (the field shows [YOUR_ID] by default) or the node will fail.
Step 6: Configure WhatsApp Dispatch
Send the AI-generated summary to WhatsApp via an HTTP API call.
- In Dispatch WhatsApp Summary, set URL to
yoururlapi.com. - Set Method to
POSTand enable Send Body. - Under Body Parameters, set phone to
[YOUR_PHONE]and message to{{ $json.output }}. - Credential Required: Connect your
httpHeaderAuthcredentials in Dispatch WhatsApp Summary. - Confirm the flow continues from Dispatch WhatsApp Summary to End Placeholder.
Step 7: Test and Activate Your Workflow
Run a full test to verify feed ingestion, summarization, and message delivery.
- Click Execute Workflow to run the workflow manually from Scheduled Start.
- Verify that Combine Feeds outputs merged items and Filter Recent Entries only passes articles from the last day.
- Confirm AI Summary Builder returns a summary in its output and Dispatch WhatsApp Summary sends a message containing
{{ $json.output }}. - Once successful, toggle the workflow to Active so Scheduled Start runs automatically on schedule.
Common Gotchas
- OpenAI credentials can expire or hit billing limits. If summaries stop, check your OpenAI API key and usage limits first.
- If you’re using Wait nodes or external rendering, processing times vary. Bump up the wait duration if downstream nodes fail on empty responses.
- Your WhatsApp webhook endpoint often requires specific formatting and auth headers. If “Dispatch WhatsApp Summary” errors, check the provider logs and confirm the URL and token are still valid.
Frequently Asked Questions
About 30 minutes if you already have your feed URLs and WhatsApp endpoint.
No. You’ll paste RSS URLs, connect OpenAI, and set your webhook details in n8n.
Yes. n8n has a free self-hosted option and a free trial on n8n Cloud. Cloud plans start at $20/month for higher volume. You’ll also need to factor in OpenAI API costs, which are usually a few cents per digest depending on length.
Two options: n8n Cloud (managed, easiest setup) or self-hosting on a VPS. For self-hosting, Hostinger VPS is affordable and handles n8n well. Self-hosting gives you unlimited executions but requires basic server management.
Yes, and it’s a simple change. Update the “Scheduled Start” trigger to run weekly, then adjust the “Filter Recent Entries” logic so it includes the time window you care about. Many people also raise or lower the “Restrict Items” limit from 10 depending on how long they want the weekly roundup to be. If the summaries start feeling generic, tweak the prompt in “AI Summary Builder” so it matches your tone and preferred format.
Usually it’s the webhook URL, auth header, or token changing on the WhatsApp provider side. Re-check the “Dispatch WhatsApp Summary” HTTP Request node settings and compare them to your provider’s latest docs. If it fails only sometimes, you might be hitting rate limits, so slow down the schedule or reduce how often you send messages.
In this setup, it summarizes 10 items per run because of the “Restrict Items” node.
Often, yes, because this kind of flow benefits from merging lists, filtering, limiting, aggregating content, and then summarizing it in one consistent pass. n8n handles those multi-step transformations cleanly, and self-hosting means you can run it as often as you want without paying per tiny step. Zapier or Make can still work, but the task history and step limits get annoying once you start combining multiple feeds and doing AI summarization. If you want to add branching logic (different digests for different topics) n8n is usually the calmer place to build. Talk to an automation expert if you want a quick recommendation based on your volume.
One daily WhatsApp message beats four feeds and a dozen half-open tabs. Set it up once, then let the workflow handle the repeatable part.
Need Help Setting This Up?
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