Block 1 - Google Gemini Chat Model
- Type / Role
- @n8n/n8n-nodes-langchain.lmChatGoogleGemini - lmChatGoogleGemini
- Config choices
- Version 1
This workflow is provided as-is. Please review and test before using in production.
LinkedIn Viral Post Scraper + AI Content Generator with Auto Publishing Who's it for Content creators, social media managers, marketing agencies, and LinkedIn growth hackers who want to automate th...
@n8n/n8n-nodes-langchain.lmchatgooglegemini, n8n-nodes-base.scheduletrigger, n8n-nodes-base.googlesheets, n8n-nodes-base.splitinbatches, n8n-nodes-base.httprequest, n8n-nodes-base.wait, n8n-nodes-base.filter, n8n-nodes-base.googlesheetstrigger
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Roshan Ramani.
Original n8n.io sourceContent creators, social media managers, marketing agencies, and LinkedIn growth hackers who want to automate their content strategy by analyzing viral posts and generating original, high-engagement content at scale.
This comprehensive automation pipeline combines LinkedIn data intelligence with AI-powered content creation to build a complete content marketing system:
Data Collection Phase:
Content Generation Phase:
The workflow operates in two connected phases. The scraping phase monitors specified LinkedIn profiles, collecting high-performing posts into a centralized database. When new viral content is detected, the AI analysis phase triggers automatically, identifying trending topics and creating original content that leverages proven engagement patterns while maintaining authenticity.
APIs and Credentials:
Setup Prerequisites:
Content Targeting: Modify the profile list in Google Sheets to focus on specific industries, thought leaders, or competitors in your niche.
Engagement Thresholds: Adjust the filter conditions to be more or less selective about which posts qualify as "viral" content.
AI Voice Customization: Edit the comprehensive system prompt in the LinkedIn Content Strategy AI node to match your brand personality, industry terminology, and content style preferences.
Visual Branding: Customize image generation prompts to include your brand colors, logo elements, or specific visual styles.
Publishing Schedule: Modify the trigger frequency and add conditional logic to publish at optimal times for your audience.
Data Retention: Add cleanup nodes to manage historical data and prevent Google Sheets from becoming unwieldy over time.
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.
| Workflow | Automate LinkedIn content using viral post analysis with Gemini AI & Flux image generation |
|---|---|
| Complexity | advanced |
| Nodes | 20 |
| Categories | Content Creation, Multimodal AI |
| Author | Roshan Ramani |
| Published | 28 Aug 2025 |
Use the JSON export at /data/workflows/7973/7973.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.
LinkedIn Viral Post Scraper + AI Content Generator with Auto Publishing Who's it for Content creators, social media managers, marketing agencies, and LinkedIn growth hackers who want to automate th...
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 Content Creation, Multimodal AI use case.