Workflow Templates

Build a fully local RAG chatbot using Ollama that works without tool calling — ideal for smaller open-source models like Qwen that don't support native function calls. This template lets you run a private, self-hosted AI assistant with retrieval-augmented generation using only your own hardware. How it works A Webhook receives the user's chat message A small classifier LLM (Qwen 7B) analyzes the input and decides: is this small talk, or a real question that needs the knowledge base? For small talk, a dedicated AI agent responds conversationally with chat memory For real questions, the classifier generates focused sub-queries, which are sent through a loop-based RAG pipeline: Each sub-query is embedded using BGE-M3 and matched against a Postgres PGVector store Results are filtered by a relevance score threshold (>0.4) Chunks are aggregated and deduplicated across all sub-queries An Answer Generator agent (Qwen 14B) produces a sourced answer using a strict 3-step format: short answer → sources → follow-up question Both paths use Postgres-backed chat memory for multi-turn conversations A post-processing step removes <think> tags that some reasoning models produce Set up steps Install Ollama and pull the required models: ollama pull qwen2.5:7b (classifier + small talk) ollama pull qwen3:14b (answer generation) ollama pull bge-m3 (embeddings) Set up PostgreSQL with the pgvector extension enabled Create your vector store — ingest your documents into the PGVector store using BGE-M3 embeddings (you can use n8n's built-in document loaders for this) Configure credentials in n8n: Ollama connection (default: http://localhost:11434) PostgreSQL connection for both chat memory and vector store Customize the webhook path and connect it to your frontend or API client Optional: Adjust the relevance score threshold, swap models for larger/smaller ones, or modify the system prompts to match your use case

How It Works This workflow automates personalized customer journeys by analyzing CRM data, purchase history, chat interactions, and performance metrics to intelligently route customer actions through multiple channels (email, SMS, retargeting) via AI-optimized schemas. A webhook trigger initiates the process by fetching CRM customer data, which is then merged with historical records and interactions. OpenAI builds comprehensive customer state profiles, enabling intelligent routing to appropriate channels using optimized journey logic. The system aggregates performance metrics in real-time and updates the database to maintain synchronized customer information across all systems. Setup Steps Connect CRM credentials (source system) Add OpenAI API key for state builder Configure Gmail/SMS provider credentials Add Google Sheets connection for performance tracking Set Touchpoint Event Webhook URL Map database connection for customer state persistence Prerequisites OpenAI API key, CRM access, Gmail/SMS provider accounts, Google Sheets, database (PostgreSQL/MySQL), n8n instance with webhook enabled. Use Cases E-commerce personalization, SaaS customer retention, multi-touch marketing automation Customization Modify journey schemas in Journey Optimizer AI, adjust routing rules in Action Type Router Benefits Reduces manual campaign management 80%, improves conversion via AI personalization

Shopify Product-to-Blog Automation with Perplexity web search, Gemini AI Agent & Google Sheets Shopify Blog Automation (From Shopify product to SEO-optimized blog post — fully automated) This workflow is an advanced n8n-powered automation that transforms newly created Shopify products into professionally written, SEO-ready blog posts using AI. By combining **Shopify Webhooks, Google Sheets, AI research, structured content generation, and automated HTML formatting**, this workflow removes all manual work from product-based content marketing. 💡 Key Advantages This Shopify Product-to-Blog Automation delivers the following benefits: 🛍️ Shopify Product Sync Automatically captures new product data (title, description, vendor, type, images) the moment a product is created. 🧠 AI-Powered Research & Writing Uses AI to perform market analysis, identify customer intent, and generate structured, high-quality blog content. 📊 Google Sheets Tracking Maintains a clear audit trail of products, generated blogs, and publishing status to prevent duplication. 🧩 Structured Content Output Generates strict JSON-based blog sections (problem, solution, features, usage, comparison, CTA) for consistency and scalability. 📤 End-to-End Automation Handles everything — from product detection to blog publishing — with zero manual writing. ⚙️ How It Works Step-by-Step Process Shopify Trigger Listens for products/create events in Shopify. Product Data Extraction Normalizes product fields and selects the primary product image. Google Sheets Storage Stores raw product data and sets initial processing status. AI Market & SEO Research Analyzes product intent, audience, use cases, FAQs, and keyword opportunities. AI Blog Content Generation Creates structured, SEO-focused blog content using a LangChain AI agent. HTML Structuring Cleans, escapes, and formats content into Shopify-safe, responsive HTML. Shopify Blog Publishing Automatically posts the article to the Shopify Blog via Admin API. Status Update & Tracking Updates Google Sheets to reflect successful blog publication. 🛠️ Setup Steps Required Node Configuration To run this workflow, configure the following nodes: Shopify Trigger** – Detect new product creation Set Node** – Normalize Shopify product fields Google Sheets Nodes** – Store and track workflow state AI Research Node** – Market & SEO analysis LangChain / Gemini Agent** – Blog content generation Code Node** – HTML formatting and safety handling HTTP Request Node** – Publish blog post to Shopify Error Handling Logic** – Retry and fail-safe routing 🔐 Credentials Required Before enabling the workflow, configure these credentials: Shopify Admin API Access Token** – For blog publishing Google Sheets OAuth** – For data tracking Google Gemini API Key** – For AI content generation Perplexity API Key** – For research and SEO insights 👤 Ideal For This automation is ideal for: Shopify store owners using content marketing Ecommerce teams managing large product catalogs SEO teams scaling product-driven blog content Agencies offering automated Shopify SEO solutions 💬 Bonus Tip This workflow is fully modular and extensible. You can easily enhance it to: Auto-link blogs to products Generate multilingual blog posts Schedule delayed publishing Route content by product category Add internal linking or schema markup All extensions can be implemented within the same n8n workflow. ✅ Result Every new Shopify product automatically becomes: Research-backed SEO-optimized Professionally structured Automatically published No manual writing. No copy-paste. Fully automated. Keywords shopify ai shopify automation shopify marketing automation shopify blog automation shopify content automation ai blog generator shopify shopify seo automation ecommerce automation ai ecommerce automation shopify workflow automation shopify product to blog auto generate shopify blogs shopify ai content how to automate shopify

How it works 🧠 AI-Powered News Update Bot for Zalo using Gemini and RSS Feeds This workflow allows you to build a smart Zalo chatbot that automatically summarizes and delivers the latest news using Google Gemini and RSS feeds. It’s perfect for keeping users informed with AI-curated updates directly inside Vietnam’s most popular messaging app. 🚀 What It Does Receives user messages via Zalo Bot webhook Fetches the latest articles from an RSS feed (e.g., AI news) Summarizes the content using Google Gemini Formats the response and sends it back to the user on Zalo 📱 What Is Zalo? Zalo is Vietnam’s leading instant messaging app, with over 78 million monthly active users—more than 85% of the country’s internet-connected population. It handles 2 billion messages per day and is deeply embedded in Vietnamese daily life, making it a powerful channel for communication and automation. 🔧 Setup Instructions 1. Create a Zalo Bot Open the Zalo app and search for "Zalo Bot Creator" Tap "Create Zalo Bot Account" Your bot name must start with "Bot" (e.g., Bot AI News) After creation, Zalo will send you a message containing your Bot Token 2. Configure the Webhook Replace [your-webhook URL] in Zalo Bot Creator with your n8n webhook URL Use the Webhook node in this workflow to receive incoming messages 3. Set Up Gemini Add your Gemini API key to the HTTP Request node labeled Summarize AI News Customize the prompt if you want a different tone or summary style 4. Customize RSS Feed Replace the default RSS URL with your preferred news source You can use any feed that provides timely updates (e.g., tech, finance, health) 🧪 Example Interaction User: "What's new today?" Bot: "🧠 AI Update: Google launches Gemini 2 with multimodal capabilities, revolutionizing how models understand text, image, and code..." ⚠️ Notes Zalo Bots currently do not support images, voice, or file attachments Make sure your Gemini API key has access to the model you're calling RSS feeds should be publicly accessible and well-formatted 🧩 Nodes Used Webhook HTTP Request (Gemini) RSS Feed Read Set & Format Zalo Message Sender (via API) 💡 Tips You can swap Gemini with GPT-4 or Claude by adjusting the API call Add filters to the RSS node to only include articles with specific keywords Use the Function node to personalize responses based on user history Built by Nguyen Thieu Toan (Nguyễn Thiệu Toàn) (https://nguyenthieutoan.com). Read more about this workflow by Vietnamese: https://nguyenthieutoan.com/share-workflow-n8n-zalo-bot-cap-nhat-tin-tuc/

Disclaimer Please note - This workflow is only available on n8n self-hosted as it's making use of the community node for the Decodo Web Scraping This workflow automates intelligent keyword and topic extraction from Google Search results, combining Decodo’s advanced scraping engine with OpenAI GPT-4.1-mini’s semantic analysis capabilities. The result is a fully automated keyword enrichment pipeline that gathers, analyzes, and stores SEO-relevant insights. Who this is for This workflow is ideal for: SEO professionals** who want to extract high-value keywords from competitors. Digital marketers** aiming to automate topic discovery and keyword clustering. Content strategists** building data-driven content calendars. AI automation engineers** designing scalable web intelligence and enrichment pipelines. Growth teams** performing market and search intent research with minimal effort. What problem this workflow solves Manual keyword research is time-consuming and often incomplete. Traditional keyword tools only provide surface-level data and fail to uncover contextual topics or semantic relationships hidden in search results. This workflow solves that by: Automatically scraping live Google Search results for any keyword. Extracting meaningful topics, related terms, and entities using AI. Enriching your keyword list with semantic intelligence to improve SEO and content planning. Storing structured results directly in n8n Data Tables for trend tracking or export. What this workflow does Here’s a breakdown of the flow: Set the Input Fields – Define your search query and target geo (e.g., “Pizza” in “India”). Decodo Google Search – Fetches organic search results using Decodo’s web scraping API. Return Organic Results – Extracts the list of organic results and passes them downstream. Loop Over Each Result – Iterates through every search result description. Extract Keywords and Topics – Uses OpenAI GPT-4.1-mini to identify relevant keywords, entities, and thematic topics from each snippet. Data Enrichment Logic – Checks whether each result already exists in the n8n Data Table (based on URL). Insert or Skip – If a record doesn’t exist, inserts the extracted data into the table. Store Results – Saves both enriched search data and Decodo’s original response to disk. End Result: A structured and deduplicated dataset containing URLs, keywords, and key topics — ready for SEO tracking or further analytics. Setup Pre-requisite If you are new to Decode, please signup on this link visit.decodo.com Please make sure to install the n8n custom node for Decodo. Import and Configure the Workflow Open n8n and import the JSON template. Add your credentials: Decodo API Key under Decodo Credentials account. OpenAI API Key under OpenAI Account. Define Input Parameters Modify the Set node to define: search_query: your keyword or topic (e.g., “AI tools for marketing”) geo: the target region (e.g., “United States”) Configure Output The workflow writes two outputs: Enriched keyword data → Stored in n8n Data Table (DecodoGoogleSearchResults). Raw Decodo response → Saved locally in JSON format. Execute Click Execute Workflow or schedule it for recurring keyword enrichment (e.g., weekly trend tracking). How to customize this workflow Change AI Model** — Replace gpt-4.1-mini with gemini-1.5-pro or claude-3-opus for testing different reasoning strengths. Expand the Schema** — Add extra fields like keyword difficulty, page type, or author info. Add Sentiment Analysis** — Chain a second AI node to assess tone (positive, neutral, or promotional). Export to Sheets or DB** — Replace the Data Table node with Google Sheets, Notion, Airtable, or MySQL connectors. Multi-Language Research** — Pass a locale parameter in the Decodo node to gather insights in specific languages. Automate Alerts** — Add a Slack or Email node to notify your team when high-value topics appear. Summary Search & Enrich is a low-code AI-powered keyword intelligence engine that automates research and enrichment for SEO, content, and digital marketing. By combining Decodo’s real-time SERP scraping with OpenAI’s contextual understanding, the workflow transforms raw search results into structured, actionable keyword insights. It eliminates repetitive research work, enhances content strategy, and keeps your keyword database continuously enriched — all within n8n.

⚠️ IMPORTANT: This template requires self-hosted n8n hosting due to the use of community nodes (MCP tools). It will not work on n8n Cloud. Make sure you have access to a self-hosted n8n instance before using this template. Overview This workflow automation allows a Google Gemini-powered AI Agent to orchestrate multi-source web intelligence using MCP (Model Context Protocol) tools such as Firecrawl, Brave Search, and Apify. The system allows users to interact with the agent in natural language, which then leverages various external data collection tools, processes the results, and automatically organizes them into structured spreadsheets. With built-in memory, flexible tool execution, and conversational capabilities, this workflow acts as a multi-agent research assistant, capable of retrieving, synthesizing, and delivering actionable insights in real time. How the system works AI Agent + MCP Pipeline User Interaction A chat message is received and forwarded to the AI Agent. AI Orchestration The agent, powered by Google Gemini, decides which MCP tools to invoke based on the query. Firecrawl-MCP: Recursive web crawling and content extraction. Brave-MCP: Real-time web search with structured results. Apify-MCP: Automation of web scraping tasks with scalable execution. Memory Management A memory module stores context across conversations, ensuring multi-turn reasoning and task continuity. Spreadsheet automation Results are structured in a new, automatically created Google Spreadsheet, enriched with formatting and additional metadata. Data processing The workflow generates the spreadsheet content, updates the sheet, and improves results via HTTP requests and field edits. Delivery of results Users receive a structured and contextualized dataset ready for review, analysis, or integration into other systems. Configuration instructions Estimated setup time: 45 minutes Prerequisites Self-hosted n8n instance (v0.200.0 or higher recommended) Google Gemini API key MCP-compatible nodes (Firecrawl, Brave, Apify) configured Google Sheets credentials for spreadsheet automation Detailed configuration steps Step 1: Configuring the AI Agent AI Agent node**: Select Google Gemini as the LLM model Configure your Google Gemini API key in the n8n credentials Set the system prompt to guide the agent's behavior Connect the Simple Memory node to enable context tracking Step 2: Integrating MCP Tools Firecrawl-MCP Configuration**: Install the @n8n/n8n-nodes-firecrawl-mcp package Configure your Firecrawl API key Set crawling parameters (depth, CSS selectors) Brave-MCP configuration**: Install the @n8n/n8n-nodes-brave-mcp package Add your Brave Search API key Configure search filters (region, language, SafeSearch) Apify-MCP configuration**: Install the @n8n/n8n-nodes-apify-mcp package Configure your Apify credentials Select the appropriate actors for your use cases Step 3: Spreadsheet automation “Create Spreadsheet” node**: Configure Google Sheets authentication (OAuth2 or Service Account) Set the file name with dynamic timestamps Specify the destination folder in Google Drive “Generate Spreadsheet Content” node**: Transform the agent's outputs into tabular format Define the columns: URL, Title, Description, Source, Timestamp Configure data formatting (dates, links, metadata) “Update Spreadsheet” node**: Insert the data into the created sheet Apply automatic formatting (headers, colors, column widths) Add summary formulas if necessary Step 4: Post-processing and delivery “Data Enrichment Request” node** (formerly “HTTP Request1”): Configure optional API calls to enrich the data Add additional metadata (geolocation, sentiment, categorization) Manage errors and timeouts “Edit Fields” node**: Refine the final dataset (metadata, tags, filters) Clean and normalize the data Prepare the final response for the user Structure of generated Google Sheets Default columns | Column | Description | Type | |---------|-------------|------| | URL | Data source URL | Hyperlink | | Title | Page/resource title | Text | | Description | Description or content excerpt | Long text | | Source | MCP tool used (Brave/Firecrawl/Apify) | Text | | Timestamp | Date/time of collection | Date/Time | | Metadata | Additional data (JSON) | Text | Automatic formatting Headings**: Bold font, colored background URLs**: Formatted as clickable links Dates**: Standardized ISO 8601 format Columns**: Width automatically adjusted to content Use cases Business and enterprise Competitive analysis combining search, crawling, and structured scraping Market trend research with multi-source aggregation Automated reporting pipelines for business intelligence Research and academia Literature discovery across multiple sources Data collection for research projects Automated bibliographic extraction from online sources Engineering and development Discovery of APIs and documentation Aggregation of product information from multiple platforms Scalable structured scraping for datasets Personal productivity Automated creation of newsletters or knowledge hubs Personal research assistant compiling spreadsheets from various online data Key features Multi-source intelligence Firecrawl for deep crawling Brave for real-time search Apify for structured web scraping AI-driven orchestration Google Gemini for reasoning and tool selection Memory for multi-turn interactions Context-based adaptive workflows Structured data output Automatic spreadsheet creation Data enrichment and formatting Ready-to-use datasets for reporting Performance and scalability Handles multiple simultaneous tool calls Scalable web data extraction Real-time aggregation from multiple MCPs Security and privacy Secure authentication based on API keys Data managed in Google Sheets / n8n Configurable retention and deletion policies Technical architecture Workflow User query → AI agent (Gemini) → MCP tools (Firecrawl / Brave / Apify) → Aggregated results → Spreadsheet creation → Data processing → Results delivery Supported data types Text and metadata** from crawled web pages Search results** from Brave queries Structured data** from Apify scrapers Tabular reports** via Google Sheets Integration options Chat interfaces Web widget for conversational queries Slack/Teams chatbot integration REST API access points Data sources Websites (via Firecrawl/Apify) Search engines (via Brave) APIs (via HTTP Request enrichment) Performance specifications Query response: < 5 seconds (search tasks) Crawl capacity: Thousands of pages per run Spreadsheet automation: Real-time creation and updates Accuracy: > 90% when using combined sources Advanced configuration options Customization Set custom prompts for the AI Agent Adjust the spreadsheet schema for reporting needs Configure retries for failed tool runs Analytics and monitoring Track tool usage and costs Monitor crawl and search success rates Log queries and outputs for auditing Troubleshooting and support Timeouts:** Manually re-run failed MCP executions Data gaps:** Validate Firecrawl/Apify selectors Spreadsheet errors:** Check Google Sheets API quotas

🚀 Overview This workflow automates video uploads from Telegram directly to Google Drive, complete with smart file renaming, Google Sheets logging, and AI assistance via Google Gemini. It’s perfect for creators, educators, or organizations that want to streamline video submissions and file management. ⚙️ How It Works Telegram Trigger -> Start the workflow when a user sends a video file to your Telegram bot. Switch Node -> Detects file type or command and routes the flow accordingly. Get File -> Downloads the Telegram video file. Upload to Google Drive -> Automatically uploads the video to your chosen Drive folder. Smart Rename -> The file name is auto-formatted using dynamic logic (date, username, or custom tags). Google Sheets Logging -> Appends or updates upload data (e.g., filename, sender, timestamp) for easy tracking. AI Agent Integration -> Uses Google Gemini AI connected to Data Vidio memory to analyze or respond intelligently to user queries. Telegram Notification -> Sends confirmation or status messages back to Telegram. 🧠 Highlights Seamlessly integrates Telegram → Google Drive → Google Sheets → Gemini AI Supports file update or append mode Auto-rename logic via the Code node Works with custom memory tools for smarter AI responses Easy to clone and adapt, just connect your own credentials 🪄 Ideal Use Cases Video assignment submissions for schools or academies Media upload management for marketing teams Automated video archiving and AI-assisted review Personal Telegram-to-Drive backup assistant 🧩 Setup Tips Copy and use the provided Google Sheet template (SheetTemplate) Configure your Telegram Bot token, Google Drive, and Sheets credentials Update the AI Agent node with your Gemini API key and connect the Data Vidio sheet Test with a sample Telegram video before full automation

This is an exaple of advanced automated data extraction and enrichment pipeline with ScrapeGraphAI. Its primary purpose is to systematically scrape the n8n community workflows website, extract detailed information about recently added workflows, process that data using multiple AI models, and store the structured results in a Google Sheets spreadsheet. This workflow demonstrates a sophisticated use of n8n to move beyond simple API calls and into the realm of intelligent, AI-driven web scraping and data processing, turning unstructured website content into valuable, structured business intelligence. Key Advantages ✅ Full Automation: Once triggered (manually or on a schedule via the Schedule Trigger node), the entire process runs hands-free, from data collection to spreadsheet population. ✅ Powerful AI-Augmented Scraping: It doesn't just scrape raw HTML. It uses multiple AI agents (Google Gemini, OpenAI) to: Understand page structure to find the right data on the main list. Clean and purify content from individual pages, removing and irrelevant information. Perform precise information extraction to parse unstructured text into structured JSON data based on a defined schema (author, price, etc.). Generate intelligent summaries, adding significant value by explaining the workflow's purpose in Italian. ✅ Robust and Structured Data Output: The use of the Structured Output Parser and Information Extractor nodes ensures the data is clean, consistent, and ready for analysis. It outputs perfectly formatted JSON that maps directly to spreadsheet columns. ✅ Scalability via Batching: The Split In Batches and Loop Over Items nodes allow the workflow to process a dynamically sized list of workflows. Whether there are 5 or 50 new workflows, it will process each one sequentially without failing. ✅ Effective Data Integration: It seamlessly integrates with Google Sheets, acting as a simple and powerful database. This makes the collected data immediately accessible, shareable, and available for visualization in tools like Looker Studio. ✅ Resilience to Website Changes: By using AI models trained to understand content and context (like "find the 'Recently Added' section" or "find the author's name"), the workflow is more resilient to minor cosmetic changes on the target website compared to traditional CSS/XPath selectors. How It Works The workflow operates in two main phases: Phase 1: Scraping the Main List Trigger: The workflow can be started manually ("Execute Workflow") or automatically on a schedule. Scraping: The "Scrape main page" node (using ScrapeGraphAI) fetches and converts the https://n8n.io/workflows/ page into clean Markdown format. Data Extraction: An LLM chain ("Extract 'Recently added'") analyzes the Markdown. It is specifically instructed to identify all workflow titles and URLs within the "Recently Added" section and output them as a structured JSON array named workflows. Data Preparation: The resulting array is set as a variable and then split out into individual items, preparing them for processing one-by-one. Phase 2: Processing Individual Workflows Loop: The "Loop Over Items" node iterates through each workflow URL obtained from Phase 1. Scrape & Clean Detail Page: For each URL, the "Scrape single Workflow" node fetches the detail page. Another LLM chain ("Main content") cleans the resulting Markdown, removing superfluous content and focusing only on the core article text. Information Extraction: The cleaned Markdown is passed to an "Information Extractor" node. This uses a language model to locate and structure specific data points (title, URL, ID, author, categories, price) into a defined JSON schema. Summarization: The cleaned Markdown is also sent to a Google Gemini node ("Summarization content"), which generates a concise Italian summary of the workflow's purpose and tools used. Data Consolidation & Export: The extracted information and the generated summary are merged into a single data object. Finally, the "Add row" node maps all this data to the appropriate columns and appends it as a new row in a designated Google Sheet. Set Up Steps To run this workflow, you need to configure the following credentials in your n8n instance: ScrapeGraphAI Account: The "Scrape main page" and "Scrape single Workflow" nodes require valid ScrapeGraphAI API credentials named ScrapegraphAI account. Install the related Community node. Google Gemini Account: Multiple nodes ("Google Gemini Chat Model", "Summarization content", etc.) require API credentials for Google Gemini named Google Gemini(PaLM) (Eure). OpenAI Account: The "OpenAI Chat Model1" node requires API credentials for OpenAI named OpenAi account (Eure). Google Sheets Account: The "Add row" node requires OAuth2 credentials for Google Sheets named Google Sheets account. You must also ensure the node is configured with the correct Google Sheet ID and that the sheet has a worksheet named Foglio1 (or update the node to match your sheet's name). Need help customizing? Contact me for consulting and support or add me on Linkedin.

Quick overview This workflow collects an exported n8n workflow JSON via an n8n Form, audits it for common reliability and security issues, uses Anthropic Claude to draft a business summary and technical report, and then creates a formatted documentation page in Notion. How it works Receives a form submission with a workflow JSON file, client name, and a Notion parent page ID. Parses and validates the uploaded JSON to confirm it contains nodes and connections and extracts the workflow metadata. Analyzes the workflow graph to determine execution order, detect cycles and unreachable nodes, and generate a scored list of audit findings. Sends the audit context to Anthropic Claude (Sonnet) to generate a business-facing workflow summary and a developer-facing audit report. Converts the generated text into Notion blocks, including an audit score callout and optional warnings for cycles or unreachable nodes. Creates a new Notion page under the provided parent page and appends the blocks in batches with a short wait to avoid Notion rate limits. Setup Import the workflow and connect your Anthropic account credential to the Claude Sonnet node. No additional configuration is needed on the Anthropic side. Connect your Notion account credential to both the Create Notion Page and Append Blocks nodes. In Notion, open the page you want to use as the parent, go to Connections in the page settings, and add your integration so it has access. Activate the workflow and open the form URL. Upload an exported n8n workflow JSON file, enter the client name, and paste the 32-character Notion page ID (found in the page URL, without dashes). Submit the form and your documentation page will appear in Notion within 30 to 60 seconds depending on workflow size. Requirements Anthropic API account with access to Claude Sonnet Notion integration token with write access to the target workspace Customization Swap Claude Sonnet for any other model supported by n8n's LangChain nodes by changing the model field on the Claude Sonnet sub-node Adjust the audit scoring weights in the Audit Workflow code node to match your team's priorities, for example increasing the penalty for CRITICAL findings or adding new secret patterns to the detection list Modify the system prompt in Build Prompt to change the tone, length, or structure of the generated documentation

This n8n template demonstrates how to automate blog post creation with AI and WordPress This workflow is designed for creators who want to maintain an active blog without spending hours writing — while still taking advantage of SEO benefits. It connects OpenAI and WordPress to help you schedule AI-generated posts or create content from simple one- or two-word prompts. 🧠 Good to know At the time of writing, each AI-generated post will use your OpenAI API credits according to your model and usage tier. This workflow requires an active WordPress site with API access and your OpenAI API key. Setup is quick — in less than 5 minutes, you can have everything running smoothly! ⚙️ How it works The workflow connects to your WordPress API and your OpenAI account. You can choose between two modes: Scheduled mode: AI automatically creates and publishes posts based on your defined schedule. Prompt mode: Enter a short phrase (one or two words) and let AI generate a complete SEO-optimized post. The generated content is formatted and published directly to your WordPress blog. You can easily customize prompts, post styles, or scheduling frequency to match your brand and goals. 🚀 How to use Start with the Manual Trigger node (as an example) — or replace it with other triggers such as webhooks, cron jobs, or form submissions. Adjust your OpenAI prompts to fine-tune the tone, structure, or SEO focus of your posts. You can also extend this workflow to automatically share posts on social media or send notifications when new articles go live. ✅ Requirements Active OpenAI API key WordPress site** with API access 🧩 Customising this workflow AI-powered content creation can be adapted for many purposes. Try using it for: Automated content calendars Generating product descriptions Creating newsletter drafts Building SEO-focused blogs effortlessly

An intelligent n8n workflow that automates your entire blog content pipeline—from keyword research to WordPress publishing. Using Google Gemini, DeepSeek, and Perplexity, this workflow generates SEO-optimized blog posts and publishes them automatically while tracking everything in Google Sheets. What this workflow does This automation handles your complete blog creation process: Scheduled content research:** Fetches approved topics from Google Sheets and conducts deep SEO research using Perplexity AI-powered writing:** Uses DeepSeek for competitor analysis and Google Gemini to write 800-1000 word SEO-optimized articles with FAQs Automated publishing:** Publishes directly to WordPress via REST API and updates tracking in Google Sheets Smart scheduling:** Runs daily at 7 AM, respects weekly frequency settings, and processes multiple clients in batches Setup requirements Tools you'll need: Active n8n instance (self-hosted or n8n Cloud) Google Sheets with OAuth access WordPress site with REST API enabled API keys: Google Gemini, DeepSeek, Perplexity (optional) Estimated setup time: 20-25 minutes Step-by-step setup 1. Prepare your Google Sheets Create two sheets: Client projects sheet: Columns: Client ID | Website URL | Blog API | GMB Name | Weekly Frequency | On Page Sheet Example: CLIENT001 | https://example.com | xxxx xxxx xxxx | Example Co | Mon,Wed,Fri | Sheet URL Content topics sheet (one per client, named "Content Requirement & Posting"): Columns: S.No. | Focus Keyword | Content Topic | Internal Linking URLs | Words | Topic Approval | Content Approval | Publish URLs | Weekly Frequency Example: 1 | best investment tips | Top 10 Investment Tips | https://example.com/page | 1000 | Approved | Approved | (empty) | Mon,Wed 2. Connect Google Sheets In n8n: Credentials → Add credential → Google Sheets OAuth2 API Complete OAuth authentication Open "Load Active Client Projects" node → Select your client sheet URL and credential Open "Get Approved Blog Topics from Sheet" node → Select credential (document URL is dynamic) 3. Add AI API credentials Google Gemini: Get API key: https://makersuite.google.com/app/apikey Add credential in n8n: Google PaLM API Select in "Gemini - Content Writing Model" node DeepSeek: Get API key: https://platform.deepseek.com/ Add credential in n8n: DeepSeek API Select in "DeepSeek - Research Model" node Perplexity (optional): Get API key: https://www.perplexity.ai/settings/api Add credential in n8n: Perplexity API Select in "Perplexity - Web Search Tool" node 4. Set up WordPress WordPress admin → Users → Profile → Application Passwords Create new application password (format: xxxx xxxx xxxx xxxx xxxx xxxx) Add to your Google Sheet: Blog API column: Paste application password Website URL column: Enter full URL (e.g., https://example.com) 5. Configure schedule Open "Daily Blog Publishing Schedule" node Set time (recommended: 7:00 AM) Choose timezone Save settings 6. Test and activate Add one test row in your sheets with today's day in Weekly Frequency Click "Daily Blog Publishing Schedule" → Execute node Verify: Blog published in WordPress, URL updated in Google Sheet Toggle workflow Active at the top How it works 1. Schedule & filtering (7 AM daily) Loads client projects from Google Sheets Filters clients by Weekly Frequency (e.g., only those publishing today) 2. Content fetching Loops through each client Fetches approved topics (Topic Approval = "Approved", Publish URLs = empty) Selects first pending topic 3. AI content creation Research phase:** DeepSeek + Perplexity analyze competitors, search intent, content gaps, LSI keywords Writing phase:** Google Gemini writes 800-1000 word article with FAQs in conversational English 4. Publishing Extracts title and body content Publishes to WordPress via REST API Updates Google Sheet with publish URL Continues to next topic/client Key features ✅ Automated research: Deep competitor analysis and SEO insights with Perplexity ✅ Dual AI models: DeepSeek for research, Gemini for writing ✅ SEO optimized: Natural keyword integration, LSI keywords, FAQs ✅ Batch processing: Handles multiple clients and topics in one run ✅ Smart scheduling: Publishes only on specified weekdays ✅ Complete tracking: End-to-end visibility in Google Sheets ✅ WordPress ready: Direct publishing with proper HTML formatting Troubleshooting Google Sheets not connecting: Re-authenticate OAuth credentials Verify sheet URLs and column names match exactly (case-sensitive) Check sharing permissions on sheets AI API errors: Verify API keys are active and have credits Check rate limits on API dashboards Reduce token usage if hitting limits WordPress publishing fails: Test REST API: Visit https://yoursite.com/wp-json/wp/v2/posts Verify application password is correct (with spaces) Ensure user has Author/Editor role Check Website URL includes https:// No topics being processed: Verify Topic Approval = "Approved" and Content Approval = "Approved" Ensure Publish URLs column is empty Check today's day matches Weekly Frequency setting Confirm sheet name is exactly "Content Requirement & Posting" Use cases Marketing agencies: Manage 10+ client blogs, scale without hiring writers SEO teams: Execute keyword strategies at scale with consistent quality Solo bloggers: Save 5-10 hours/week, maintain regular publishing schedule Content teams: Run company blog on autopilot with oversight and tracking Publishers: Operate multiple niche blogs, reduce costs by 70-80% Expected results Time savings:** 5-10 hours per week per client Output:** 10-20 SEO-optimized posts per week SEO impact:** Improved rankings within 2-3 months Cost efficiency:** 70-80% reduction vs. hiring writers Reliability:** Never miss a publishing deadline Workflow Customization & Next Steps This workflow (Part 1) focuses on content research and writing. To complete the full automation, you will need Part 2, which you will get in the next post. Please ensure you set it up as well, as it manages WordPress publishing along with featured images. Resources n8n documentation Google Gemini API DeepSeek API docs WordPress REST API Support Need help or custom development? 📧 Email: info@isawow.com 🌐 Website: https://isawow.com/

Overview This workflow automates the discovery, extraction, enrichment, and storage of business information from Google Maps search queries using AI tools, scrapers, and Google Sheets. It is ideal for: Lead generation agencies Local business researchers Digital marketing firms Automation & outreach specialists 🔧 Tools & APIs Used Google Maps Search (via HTTP)** Custom JavaScript Parsing** URL Filtering & De-duplication** Google Sheets (Read/Write)** APIFY Actor** for business scraping LangChain AI Agent** (OpenRouter - Gemini 2.5) n8n Built-in Logic** (Loops, Conditions, Aggregators) 🧠 Workflow Summary Trigger The automation starts via schedule (every hour). Read Queries from Google Sheet Loads unprocessed keywords from a Google Sheet tab named keywords. Loop Through Keywords Each keyword is used to search Google Maps for relevant businesses. Extract URLs JavaScript parses HTML to find all external website URLs from the search results. Clean URLs Filters out irrelevant domains (e.g., Google-owned, example.com, etc.), and removes duplicates. Loop Through URLs For each URL: Checks if it already exists in the Google Sheet (to prevent duplication). Calls the APIFY Actor to extract full business data. Optionally uses AI Agent (Gemini) to provide detailed insight on the business, including: Services, About, Market Position, Weaknesses, AI suggestions, etc. Converts the AI result (text) to a structured JSON object. Save to Google Sheet Adds all extracted and AI-enriched business information to a separate tab (Sheet1). Mark Queries as Processed Updates the original row in keywords to avoid reprocessing. 🗃️ Output Fields Saved The following information is saved per business: Business Name, Website, Email, Phone Address, City, Postal Code, Country, Coordinates Category, Subcategory, Services About Us, Opening Hours, Social Media Links Legal Links (Privacy, Terms) Logo, Languages, Keywords AI-Generated Description** Google Maps URL 📈 Use Cases Build a prospect database for B2B cold outreach. Extract local SEO insights per business. Feed CRMs or analytics systems with enriched business profiles. Automate market research for regional opportunity detection. 📩 Want a Similar Workflow? If you’d like a custom AI-powered automation like this for your business or agency, feel free to contact me: 📧 msaidwolfltd@gmail.com