Write JSON to disk (binary)
The “Write Binary File” expects binary data. The JSON data is, however, JSON ;) There should really be a node that allows moving data around between both of them. For now, it can be done with a Function-Node. At least till a proper one is in place. The first node is example data, wich you can customize or replace. The second node named “Make Binary” is the important one with the custom code which makes the data binary and writes it to the correct location.
By mikeCreate SEO-optimized WordPress blogs automatically with Perplexity & Google Trends
AI Blog Automation System Description This comprehensive N8N automation template revolutionizes content creation by delivering a complete end-to-end solution for AI-powered blog generation. Transform simple ideas into fully SEO-optimized, WordPress-ready articles that rank higher and drive organic traffic to your website. The system accepts blog requests from multiple communication channels (Telegram, WhatsApp, Slack, Gmail) and automatically processes them through an intelligent pipeline that includes advanced keyword research, competitor analysis, and market insights. Using cutting-edge AI models like GPT-4 and OpenRouter, the workflow generates detailed content outlines, conducts comprehensive research, and produces high-quality, engaging blog posts that are automatically formatted and published directly to your WordPress website. What sets this template apart is its focus on SEO excellence - every piece of content is optimized for search engines with proper keyword density, meta descriptions, internal linking strategies, and content structure that search engines love. The integrated content tracking system maintains a database of all published articles, enabling smart internal linking recommendations and content performance monitoring. Key Features 🤖 Advanced AI Content Generation GPT-4 & OpenRouter Integration - Leverage the most powerful AI models for superior content quality Multi-stage content refinement - From outline to final polish, ensuring professional-grade articles Topic research and fact-checking - AI conducts deep research to create authoritative, well-sourced content 🎯 SEO Optimization at Every Step Intelligent keyword research - Automatic discovery of high-volume, low-competition keywords Competitor analysis - Analyze top-ranking content to identify content gaps and opportunities On-page SEO optimization - Perfect keyword density, meta descriptions, and heading structure Internal linking strategy - Smart recommendations for linking to existing content SEO-friendly URL generation - Automatically create search-engine optimized permalinks 🔌 Seamless WordPress Integration Direct publishing - Articles go live on your WordPress site without manual intervention Custom post formatting - Proper heading tags, featured images, and category assignment Draft and scheduling options - Choose immediate publishing or schedule for optimal timing Media handling - Automatic image optimization and alt-text generation 📱 Multi-Platform Input System Telegram, WhatsApp, Slack, Gmail support - Accept blog ideas from your preferred communication channels Voice message transcription - Convert audio ideas into written blog requests Email parsing - Extract blog topics from client emails or team communications Priority queue management - Handle multiple requests efficiently with smart prioritization 📊 Content Management & Analytics Comprehensive content database - Track all published articles, keywords, and performance metrics Internal linking opportunities - Automatic suggestions for connecting related content Publishing schedule optimization - AI-recommended posting times for maximum engagement Performance tracking - Monitor which topics and keywords drive the most traffic 📋 Complete Setup Guide Included This template comes with a comprehensive step-by-step setup guide that walks you through: N8N workflow installation and configuration API key setup for all integrated services (OpenAI, WordPress, communication platforms) WordPress plugin installation and permissions configuration Database setup for content tracking and analytics Custom field configuration for SEO optimization Webhook configuration for multi-platform input Testing procedures to ensure everything works perfectly Troubleshooting guide for common issues Best practices for content optimization and workflow management Perfect for content creators, digital marketers, SEO specialists, and enterprises looking to scale their content production while maintaining high quality and search engine visibility. Whether you're managing a single blog or multiple WordPress sites, this automation system transforms your content workflow from manual labor to intelligent automation.
By PaulDaily topic news digest with Gemini AI, Decodo MCP and Slack
Try It Out! This n8n template demonstrates how to build an autonomous AI news agent using Decodo MCP that automatically finds, scrapes, and delivers fresh industry news to your team via Slack. Use cases are many – automated news monitoring for your industry, competitive intelligence gathering, startup monitoring, regulatory updates, research automation, or daily briefings for your organization. How it works Define your news topics using the Set node – AI, MCP, web scraping, whatever matters to your business. The AI Agent processes those topics using the Gemini Chat Model, determining which tools to use and when. Here's where it gets interesting: Decodo MCP gives your AI agent the tools to search Google, scrape websites, and parse content automatically – all while bypassing geo-restrictions and anti-bot measures. The agent hunts for fresh articles from the last 48 hours, extracts clean data, and returns structured JSON results. Format Results cleans up the AI's messy output and removes duplicates. Your polished news digest gets delivered to Slack with clickable links and summaries. How to use Schedule trigger runs daily at 9 AM – adjust timing or swap for webhook triggers as needed. Customize topics in the Set node to match your industry. Scales effortlessly: add more topics, tweak search criteria, done. Requirements Decodo MCP credentials (free trial available) – grab the Smithery connection URL with keys and paste it straight into your n8n MCP node. Done. Gemini API key for the AI processing – drop it into the Google Gemini Chat Model node and pick whichever Gemini model fits your needs. Slack workspace for delivery – n8n's Slack integration docs have you covered. What the final output looks like Here's what your team receives in Slack every morning: Need help? Join the Discord or email support@decodo.com for questions. Happy Automating!
By Satyam TripathiComplete AI safety suite: test 9 guardrail layers with Groq LLM
Who's It For AI developers, automation engineers, and teams building chatbots, AI agents, or workflows that process user input. Perfect for those concerned about security, compliance, and content safety. What It Does This workflow demonstrates all 9 guardrail types available in n8n's Guardrails node through real-world test cases. It provides a comprehensive safety testing suite that validates: Keyword blocking for profanity and banned terms Jailbreak detection to prevent prompt injection attacks NSFW content filtering for inappropriate material PII detection and sanitization for emails, phone numbers, and credit cards Secret key detection to catch leaked API keys and tokens Topical alignment to keep conversations on-topic URL whitelisting to block malicious domains Credential URL blocking to prevent URLs with embedded passwords Custom regex patterns for organization-specific rules (employee IDs, order numbers) Each test case flows through its corresponding guardrail node, with results formatted into clear pass/fail reports showing violations and sanitized text. How to Set Up Add your Groq API credentials (free tier works fine) Import the workflow Click "Test workflow" to run all 9 cases Review the formatted results to understand each guardrail's behavior Requirements n8n version 1.119.1 or later (for Guardrails node) Groq API account (free tier sufficient) Self-hosted instance (some guardrails use LLM-based detection) How to Customize Modify test cases in the "Test Cases Data" node to match your specific scenarios Adjust threshold values (0.0-1.0) for AI-based guardrails to fine-tune sensitivity Add or remove guardrails based on your security requirements Integrate individual guardrail nodes into your production workflows Use the sticky notes as reference documentation for implementation This is a plug-and-play educational template that serves as both a testing suite and implementation reference for building production-ready AI safety layers.
By Muhammad Shaheer Awan