Intelligent AI digest for security, privacy, and compliance feeds
How it works This workflow acts like your own personal AI assistant, automatically fetching and summarizing the most relevant Security, Privacy, and Compliance news from curated RSS feeds. It processes only the latest articles (past 24 hours), organizes them by category, summarizes key insights using AI, and delivers a clean HTML digest straight to your inboxβsaving you time every day. Key Highlights Handles three independent tracks: Security, Privacy, and Compliance Processes content from customizable RSS sources (add/remove easily) Filters fresh articles, removes duplicates, and sorts by recency Uses AI to summarize and format insights in a digestible format Sends polished HTML digests via Gmailβone per category Fully modular and extensibleβadapt it to your needs Personalization You can easily tailor the workflow: π― Customize feeds: Add or remove sources in the following Code nodes: Fetch Security RSS, Fetch Privacy Feeds, and Fetch Compliance Feeds π§ Modify logic: Adjust filters, sorting, formatting, or even AI prompts as needed π§ Bring your own LLM: Works with Gemini, but easily swappable for other LLM APIs Setup Instructions Requires Gmail and LLM (e.g., Gemini) credentials Prebuilt with placeholders for RSS feeds and email output Designed to be readable, maintainable, and fully adaptable
By Niranjan GSend daily weather updates via a notification in Line
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By Harshil AgrawalGenerate knowledge base articles with GPT & Perplexity AI for Contentful CMS
Workflow: Auto Knowledge Base Article Generator β‘ About the Creators This workflow was created by Varritech Technologies, an innovative agency that leverages AI to engineer, design, and deliver software development projects 500% faster than traditional agencies. Based in New York City, we specialize in custom software development, web applications, and digital transformation solutions. If you need assistance implementing this workflow or have questions about content management solutions, please reach out to our team. ποΈ Architecture Overview This workflow automates the end-to-end creation of a structured knowledge-base article from a simple chat prompt: Chat Trigger β Receives user request AI Drafting Loop β Generates & refines JSON article via AI agents Perplexity Research Call β Deep-dive content generation Editorial Loop β Up to 3 AI-driven revisions Contentful Publish β Pushes final JSON into CMS --- π¦ Node-by-Node Breakdown mermaid flowchart LR A[Webhook: Chat Trigger] --> B[AI Writer Agent] B --> C[HTTP Request: Perplexity Content] C --> D[Function: Format Output & Citations] D --> E[Loop Start: Initialize Count] E --> F[AI Editor Agent] F --> G{action == "rewrite"?} G -- yes --> H[Function: Merge Improvements] H --> I[Increment Count] --> F G -- no --> J[Stop Loop] J --> K[HTTP Request: Publish to Contentful] Webhook: Chat Trigger Type: HTTP Webhook (POST /webhook/knowledge-article) Payload: { "chatInput": "What topics should I write about?" } Purpose: Kicks off the workflow on that chat prompt. AI Writer Agent Inputs: chatInput or existing article JSON Outputs: { "title": "...", "slug": "...", "category.id": "...", "description": "...", "keywords": [...], "content": "...", "metaTitle": "...", "metaDescription": "...", "readingTime": 5, "difficulty": "intermediate" } Purpose: Generates the article skeleton (metadata + initial content). HTTP Request: Perplexity Content Method: POST URL: https://api.perplexity.ai/research Body: json { "model": "sonar-deep-research", "query": "{{ $json.title }}", "length": 1000 } Purpose: Retrieves a long-form, deeply researched draft for the article body. Function: Format Output & Citations Logic: Parse raw Perplexity response Extract source URIs Append them under a sources markdown list Editorial Loop Initialize Counter to 0 AI Editor Agent Reads draft JSON Returns either: action: "rewrite" + improvements: [...] or action: "submit" Merge Improvements (if rewriting) Applies suggested updates to JSON fields Limit Check Stops after 3 iterations or on "submit" HTTP Request: Publish to Contentful Method: PUT URL: https://cdn.contentful.com/spaces/{space}/environments/master/entries/{entryId} Headers: Authorization: Bearer <token> Content-Type: application/vnd.contentful.management.v1+json Body: Maps JSON β Contentful entry fields Outcome: Publishes the finalized article live. π Design Rationale & Best Practices Separation of Concerns Writer vs. Editor agents isolate creative drafting from quality review. Idempotent Loop Counter + action flags prevent infinite retries. Extensibility Swap in different research APIs or CMS targets with minimal changes. Structured JSON Ensures predictable input/output for each node.
By Varritechπ΅ Sync YouTube and Spotify music playlists
Workflow Overview This workflow automates the process of updating a Spotify playlist with tracks from a YouTube playlist, ensuring no duplicates are added. Key Components Manual Trigger: Starts the workflow when you click βTest workflowβ. Spotify Integration: Retrieves tracks from a specified Spotify playlist. YouTube Integration: Fetches tracks from a designated YouTube playlist. Batch Processing: Processes tracks in batches to handle multiple items efficiently. Track Search: Searches for YouTube tracks on Spotify to find corresponding IDs. Comparison: Compares existing Spotify tracks with YouTube tracks to identify which ones to add. Track Addition: Adds new Spotify tracks to the playlist that are not already included. If you have any questions or need clarification, feel free to ask!
By LouisSchedule social media posts from Google Sheets to Twitter & Instagram
Social Media Auto-Poster (Google Sheets β Twitter & Instagram) This workflow automatically: Pulls rows marked as Pending from a Google Sheet. Generates a formatted Instagram caption and HTML preview. Converts the HTML into an image via HCTI.io. Posts the content: As a tweet (text only) to Twitter (X). As a post (image + caption) to Instagram via the Facebook Graph API. Marks the row in Google Sheets as Posted with a timestamp. It runs every 5 hours (configurable via the Schedule Trigger). --- Requirements Google Sheets API Credentials connected in n8n. HCTI.io account (HTML β Image API). Twitter (X) OAuth1 credentials. Facebook/Instagram Graph API access token (for the business account/page). A Google Sheet with at least these columns: RowID Caption Desc Hashtags Status Set Status to Pending for any row you want posted. --- Setup Import the JSON workflow (My_workflow.json) into your n8n instance. Link all credentials (replace placeholders with your own API keys and tokens). Update the Google Sheet ID and Sheet Name inside the Get row(s) in sheet and Update Status Posted nodes. (Optional) Adjust the posting interval in the Schedule Trigger node. --- How It Works Trigger: Runs every 5 hours. Fetch Rows: Reads Google Sheets for rows with Status = Pending. Caption Generation: Combines Desc + Hashtags into final_caption. HTML β Image: Converts caption to a styled 1080x1080 post. Social Posting: Posts the caption to Twitter (text only). Uploads the image + caption to Instagram. Update Status: Marks the row as Posted on [timestamp]. --- Notes Facebook/Instagram tokens expire; refresh or use long-lived tokens. HCTI.io may require a paid plan for high volumes. Works best with a business Instagram account linked to a Facebook Page. --- License This workflow can be reused and adapted freely under the MIT license.
By Parag JavaleComprehensive SEO keyword research & analysis with DataForSEO and Airtable
Premium n8n Workflow: DataForSEO + Airtable Keyword Research This premium n8n workflow harnesses the power of DataForSEO's API combined with Airtable's relational database capabilities to transform your keyword research process, providing deeper insights for content creation without the hefty price tag of traditional SEO tools. --- π Features π Comprehensive Data Extracts related keywords, search volume π, keyword difficulty π, search intent π€, and more directly from DataForSEO's powerful API π. π° Cost-Effective Leverages DataForSEO's pay-as-you-go model πΈ, making it budget-friendly. ποΈ Airtable Integration Organizes your data in a powerful relational database for advanced filtering, sorting, and visualization capabilities. π Cross-Reference Capabilities Create relationships between keyword sets to identify content opportunities traditional tools miss. π€ Fully Automated Set up once and run keyword research with a single click. βοΈ Efficient & Scalable Handles large keyword lists with Airtable's robust data management system. --- π₯ This Workflow is Perfect For: Content creators π Bloggers π» YouTubers π₯ Small business owners πΌ Digital marketers π SEO professionals π Entrepreneurs π E-Commerce website owners π» Stop overspending on expensive SEO tools and start generating actionable keyword insights with a professional-grade database. --- π What's Included? βοΈ n8n Workflow Template Ready-to-use workflow with pre-configured DataForSEO API endpoints for comprehensive keyword data collection. π Airtable Database Structure Pre-built tables and fields specifically designed for SEO keyword analysis. π DataForSEO Integration Complete setup for pulling multiple data types (related keywords, suggestions, people also ask, subtopics) from DataForSEO's API. π Automated Data Processing Logic to clean, format, and structure raw API data into usable insights. π Documentation Step-by-step instructions for connecting your DataForSEO account and configuring the workflow. --- π Why Choose the Airtable Version? π± Access Anywhere: Review your keyword research on any device through Airtable's apps. π€ Team Collaboration: Share your keyword database for collaborative planning. π Data Relationships: Connect keywords, content ideas, and publishing schedules in one place. π Extensibility: Integrate with other tools via Airtable's ecosystem. π― Content Planning: Use Airtable as a complete content management system, from research to publication tracking. --- π οΈ How It Works 1οΈβ£ Import the provided n8n workflow into your n8n instance π₯. 2οΈβ£ Configure your DataForSEO API credentials and Airtable connections βοΈ. 3οΈβ£ Input your target keywords and desired parameters π. 4οΈβ£ Trigger the workflow β n8n automatically gathers and organizes your keyword research in Airtable π€. 5οΈβ£ Use Airtableβs interface to analyze relationships, identify opportunities, and plan your strategy π. Additional detailed instructions are provided in the workflow. --- π What You Need to Get Started πΉ Access to n8n (self-hosted or cloud) βοΈ πΉ A DataForSEO account with API credentials π πΉ An Airtable account (free tier works, Pro recommended for advanced features) π πΉ Basic understanding of API usage and n8n workflows π§ --- π‘ You can also connect this workflow with my SEO-Based Keyword Categorization & Clustering Strategy Workflow with Airtable and my Multi-Agent SEO Optimized Blog Writing System with Hyperlinks for E-Commerce, both available on my profile, to build a fully automated, end-to-end SEO content machine.
By GloriaTesla 1hour & 1day klines tool (Candlestick & volume AI pattern detector)
π Detect key candlestick reversal patterns and volume divergence on Tesla (TSLA) using GPT-4.1 and real-time OHLCV data. This AI agent evaluates 1-hour and 1-day candles and is an essential part of the Tesla Financial Market Data Analyst Tool. It identifies signals like Doji, Engulfing, Hammer, and volume anomalies to support trade entry and exit logic. β οΈ Not a standalone template β must be triggered by the Tesla Financial Market Data Analyst Tool π Requires: Alpha Vantage Premium API Key OpenAI GPT-4.1 access --- π What This Agent Does Calls Alpha Vantage to fetch: π 1-hour OHLCV data π 1-day OHLCV data GPT-4.1 evaluates: π Candlestick patterns like Doji, Engulfing, Shooting Star π Volume divergence (price/volume inconsistency) Returns a structured JSON output like: json { "summary": "Bearish signs detected on 1-day chart. A shooting star formed on high volume while RSI is elevated. Volume divergence seen on 1h chart as price rises but volume weakens.", "candlestickPatterns": { "1h": "None", "1d": "Shooting Star" }, "volumeDivergence": { "1h": "Bearish", "1d": "None" }, "ohlcv": { "1h": { "close": 174.1, "volume": 1430000, "high": 175.0, "low": 173.8 }, "1d": { "close": 188.3, "volume": 21234000, "high": 189.9, "low": 183.7 } } } --- π οΈ Setup Instructions Import the Workflow Name it: Tesla1hourand1dayKlines_Tool Install Dependencies β Tesla Financial Market Data Analyst Tool (this is the trigger parent) Add Required Credentials Alpha Vantage Premium β via HTTP Query Auth OpenAI GPT-4.1 β via OpenAI credentials Verify Web Access This tool fetches data live from Alpha Vantage: /query?function=TIMESERIESINTRADAY&interval=60min /query?function=TIMESERIESDAILY Run via Execute Workflow Trigger This tool will activate only when called by the Financial Analyst Agent. Inputs: message (optional) sessionId (used for memory continuity) --- π§ Agent Architecture | Component | Description | | ----------------------- | --------------------------------------------------- | | Candlestick Data Hour | Fetches 60min TSLA candles via Alpha Vantage | | Candlestick Data Day | Fetches daily TSLA candles via Alpha Vantage | | OpenAI Chat Model | GPT-4.1 reasoning engine for pattern detection | | Simple Memory | Maintains short-term logic context | | Tesla Klines Agent | LangChain AI agent analyzing both candle and volume | --- π Sticky Notes Overview π Workflow Purpose π§ Short-Term Memory Notes π 1h/1d Data Fetch Logic π Candlestick Pattern Types Detected π Volume Divergence Definitions π€ GPT-4.1 Prompt Configuration --- π Licensing & Support Β© 2025 Treasurium Capital Limited Company Logic, pattern reasoning, and prompt structure are proprietary IP. π Don Jayamaha β LinkedIn π n8n Creator Profile --- π Automate technical edge: detect TSLA candle reversals and volume anomalies with precision using GPT-4.1 and Alpha Vantage. Required by the Tesla Financial Market Data Analyst Tool.
By Don Jayamaha JrTranslate instructions using LingvaNex
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By Harshil Agrawalπ οΈ Google Cloud Firestore tool MCP server πͺ all 7 operations
Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator? Join the community Complete MCP server exposing all Google Cloud Firestore Tool operations to AI agents. Zero configuration needed - all 7 operations pre-built. β‘ Quick Setup Import this workflow into your n8n instance Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL π§ How it Works β’ MCP Trigger: Serves as your server endpoint for AI agent requests β’ Tool Nodes: Pre-configured for every Google Cloud Firestore Tool operation β’ AI Expressions: Automatically populate parameters via $fromAI() placeholders β’ Native Integration: Uses official n8n Google Cloud Firestore Tool tool with full error handling π Available Operations (7 total) Every possible Google Cloud Firestore Tool operation is included: π§ Document (6 operations) β’ Create a document β’ Create or update a document β’ Delete a document β’ Get a document β’ Get many documents β’ Query a document π§ Collection (1 operations) β’ Get many collections π€ AI Integration Parameter Handling: AI agents automatically provide values for: β’ Resource IDs and identifiers β’ Search queries and filters β’ Content and data payloads β’ Configuration options Response Format: Native Google Cloud Firestore Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic π‘ Usage Examples Connect this MCP server to any AI agent or workflow: β’ Claude Desktop: Add MCP server URL to configuration β’ Custom AI Apps: Use MCP URL as tool endpoint β’ Other n8n Workflows: Call MCP tools from any workflow β’ API Integration: Direct HTTP calls to MCP endpoints β¨ Benefits β’ Complete Coverage: Every Google Cloud Firestore Tool operation available β’ Zero Setup: No parameter mapping or configuration needed β’ AI-Ready: Built-in $fromAI() expressions for all parameters β’ Production Ready: Native n8n error handling and logging β’ Extensible: Easily modify or add custom logic > π Free for community use! Ready to deploy in under 2 minutes.
By David Ashby