Block 1 - Sticky Note11
- Type / Role
- n8n-nodes-base.stickyNote - stickyNote
- Config choices
- Version 1
This workflow is provided as-is. Please review and test before using in production.
This n8n workflow automates the process of fetching, processing, and storing tech news articles from RSS feeds into a Notion database. It retrieves articles from The Verge and TechCrunch, processes...
n8n-nodes-base.stickynote, n8n-nodes-base.noop, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.chainllm, n8n-nodes-base.notion, n8n-nodes-base.code, n8n-nodes-base.html, n8n-nodes-base.httprequest
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by moosa.
Original n8n.io sourceThis n8n workflow automates the process of fetching, processing, and storing tech news articles from RSS feeds into a Notion database. It retrieves articles from The Verge and TechCrunch, processes them to avoid duplicates, extracts full article content, generates summaries using an LLM, and stores the data in Notion. The workflow is designed to run on a schedule or manually for testing, with sticky notes providing clear documentation for each step.
Data in notion
Triggers:
When clicking ‘Execute workflow’).Schedule Trigger, disabled).Fetch Feeds:
The Verge) and TechCrunch (TechCrunch).Hash Creation:
Crypto, Crypto1) to identify unique articles efficiently.Loop Over Articles:
Loop Over Items, Loop Over Items1) to handle multiple articles from each feed.Duplicate Check:
Get many database pages, Get many database pages1) to check if an article’s hash exists. If it does, the article is skipped (If, If1).Fetch Full Article:
HTTP Request, HTTP Request1).Extract Content:
HTML, HTML1) using specific CSS selectors (.duet--article--article-body-component p for The Verge, .entry-content p for TechCrunch).Clean Data:
Code in JavaScript, Code in JavaScript1) processes the extracted content by removing empty paragraphs, links, and excessive whitespace, then joins paragraphs into a single string.Summarize Article:
OpenAI Chat Model, OpenAI Chat Model1) with a LangChain node (Basic LLM Chain, Basic LLM Chain1) to generate a concise summary (max 1500 characters) in plain text, focusing on main arguments or updates.Store in Notion:
Create a database page, Create a database page1) with fields for title, summary, date, hash, URL, source, digest status, and full article text.Credentials:
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
Showing the first 24 of 37 workflow blocks. Download the JSON for the full node graph.
| Workflow | Tech news aggregator: The Verge & TechCrunch RSS to Notion with GPT-4 summaries |
|---|---|
| Complexity | advanced |
| Nodes | 37 |
| Categories | Market Research, AI Summarization |
| Author | moosa |
| Published | 15 Sept 2025 |
Use the JSON export at /data/workflows/8600/8600.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
This n8n workflow automates the process of fetching, processing, and storing tech news articles from RSS feeds into a Notion database. It retrieves articles from The Verge and TechCrunch, processes...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Market Research, AI Summarization use case.