Templates / Scrape high-engagement LinkedIn posts and auto-post with Gemini images

Scrape high-engagement LinkedIn posts and auto-post with Gemini images

Ready for 3.0

by Roshan Ramani ✓ · 767 views · created 2026-01-21 · Content Creation, Multimodal AI

Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.

What this workflow does

This AI workflow has 17 nodes and runs on a schedule (every 12 hours) (plus 1 other trigger). Along the way it connects Google Gemini Chat Model, Google Sheets, LinkedIn and Google Gemini. It also calls api.apify.com over HTTP.

How it runs

Trigger: On a schedule (every 12 hours) (plus 1 other trigger).

  1. Fetch LinkedIn Profile URLs (Google Sheets): uses Google Sheets
  2. Filter: keeps only the items that match a condition
  3. Process Profiles in Batches (Loop Over Items (Split in Batches)): loops over the items in batches
  4. Aggregate: combines items into one
  5. Scrape LinkedIn Posts API (HTTP Request): calls api.apify.com (POST)
  6. LinkedIn Content Strategy AI (AI Agent): runs an AI agent, with model: Google Gemini Chat Model; output parser: JSON Output Parser
  7. Rate Limiting Delay (Wait): waits 3 seconds
  8. Generate an image (Google Gemini): work with image
  9. Filter: keeps only the items that match a condition
  10. Publish to LinkedIn (LinkedIn): uses LinkedIn

…plus 3 more steps. See the full node list below.

Services it uses

Google Gemini Chat ModelGoogle SheetsLinkedInGoogle Gemini

HTTP calls to: api.apify.com

Before you upgrade to n8n 3.0

Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.

Nodes used (14)

From the author

Who's it for This workflow is ideal for: - Content creators who want to replicate successful LinkedIn strategies - Social media managers monitoring competitor content performance - Marketing teams analyzing trending topics in their industry - Personal brands…

Excerpt from Roshan Ramani's description on n8n.io.

View the original on n8n.io → Check your own copy

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