Workflow Templates

Zoho CRM - Buyer Persona Matcher This workflow automates the process of identifying buyer personas and generating personalized sales outreach. It triggers via a Zoho CRM Webhook when a deal is updated, enriches the contact data by scraping LinkedIn profiles using Phantombuster and uses OpenAI to match the contact against a defined Persona Database. The final analysis, including a tailored outreach message and confidence score, is synced back to the Zoho CRM contact record. Quick Implementation Steps Set the phantombusterAgentId and personaMatchThreshold in the Workflow Configuration node. Configure your Zoho CRM Webhook to trigger on "Potentials" (Deals) updates. Connect your Phantombuster API credential to the Scrape LinkedIn Profile node. Connect your OpenAI API credential to the OpenAI Chat Model node. Connect your Zoho CRM OAuth2 credential to the CRM nodes. What It Does This workflow transforms raw CRM data into actionable sales intelligence. When a deal is identified, it retrieves the contact's LinkedIn URL and uses an external scraper to gather real-time professional data (title, experience and skills). The AI-driven core compares this live data against a structured database of target personas (e.g., Executive Decision Maker, Technical Evaluator) to: Assign a specific Buyer Persona to the contact. Calculate a Confidence Score (0-1) for the match. Generate a Personalized Outreach Message and specific Talking Points based on the contact's background. The results are automatically written back to the Zoho CRM Contact description, providing sales reps with an immediate strategy for engagement. Who’s It For Sales Development Representatives (SDRs)** wanting to automate the research phase of outbound prospecting. Account Executives (AEs)** looking for personalized talking points tailored to the specific seniority and role of their prospects. Revenue Operations (RevOps)** teams aiming to standardize persona data within the CRM based on objective professional data. Requirements to Use This Workflow A running n8n instance (self-hosted or cloud). Zoho CRM** account with "Potentials" (Deals) and "Contacts" modules. Phantombuster** account and a configured LinkedIn Profile Scraper agent. OpenAI** account (API key) for the persona matching agent. How It Works & How To Set Up Step 1: Configure Trigger and Global Variables Zoho CRM Webhook: Setup a workflow rule in Zoho CRM to trigger this webhook when a deal is updated or created. Workflow Configuration: Open this node and set your parameters: phantombusterAgentId: Your specific Phantombuster scraper ID. personaMatchThreshold: The minimum score (e.g., 0.7) required to accept an AI persona match. Step 2: External Enrichment Setup Extract Contact Data: This node pulls the LinkedIn URL from the Zoho "Next Step" or custom field. Ensure your Zoho deal records contain valid LinkedIn URLs. Scrape LinkedIn Profile: Connect your Phantombuster credentials to allow the workflow to fetch live professional details. Step 3: Define Your Personas Persona Database: Modify the JSON in this node to reflect your company's specific target buyer personas, including their characteristics and typical communication styles. OpenAI Chat Model: Connect your OpenAI API credential. It uses gpt-4o-mini by default for analysis. Step 4: CRM Synchronization Update Zoho CRM Contact: This node pushes the AI's findings (Persona, Style, Talking Points) into the CRM. Ensure the contactId mapping matches your Zoho environment. How To Customize Nodes Expand Persona Profiles Update the Persona Database node to include more niche roles or industry-specific traits to improve the AI's matching accuracy. Adjust Outreach Tone Modify the "System Message" in the Persona Matcher & Outreach Generator to change the tone of the generated messages (e.g., making them more formal or more casual). Custom Field Mapping Change the Update Zoho CRM Contact node to map the persona data into custom CRM fields instead of the default "Description" field for better reporting. Troubleshooting Guide | Issue | Possible Cause | Solution | | :--- | :--- | :--- | | No LinkedIn Data | LinkedIn URL missing or invalid format. | Ensure the Zoho field used for the URL contains a full https://linkedin.com/in/... link. | | Phantombuster Error | Agent ID is incorrect or API credits exhausted. | Verify the phantombusterAgentId in Workflow Configuration and check your Phantombuster dashboard. | | Low Confidence Scores | LinkedIn profile is too sparse or private. | The AI may need more data; ensure the scraper is successfully pulling the "About" and "Experience" sections. | | CRM Update Failing | OAuth2 connection expired. | Re-authenticate your Zoho CRM OAuth2 credentials in n8n. | Need Help? If you need help tailoring the AI persona matching logic, integrating additional data scrapers or mapping these insights into specific CRM dashboards, please reach out to our n8n workflow developers at WeblineIndia. We can help you scale your personalized outreach and increase your conversion rates.

Automatically retrieve AWS invoices and create corresponding bills in FreeAgent, marking them as paid. This workflow eliminates manual data entry for AWS billing. What It Does Fetches invoices from AWS Invoicing API for the previous month Filters invoices by issue date to ensure only new ones are processed Checks PostgreSQL database for previously processed invoices Creates a bill in FreeAgent with correct dates and amounts Marks the bill as paid with a bank transaction explanation Records the invoice in the database to prevent future duplication Prerequisites AWS account with Invoicing API access FreeAgent account with OAuth API access PostgreSQL database (you could modify to use n8n Data Table?) AWS IAM user with invoicing:ListInvoiceSummaries permission Quick Setup Checklist [ ] Create PostgreSQL table (see below) [ ] Add PostgreSQL credentials in n8n [ ] Set up FreeAgent OAuth2 credentials [ ] Update AWS access key and secret key in "Generate AWS Signature" node [ ] Update AWS account ID in "Calculate Last Month" node [ ] Get and update FreeAgent contact ID for AWS [ ] Get and update FreeAgent category ID (cloud services/hosting) [ ] Get and update FreeAgent bank account ID Configuration Required This template has placeholders that you need to replace: In Code Nodes YOUR_AWS_ACCESS_KEY_ID - Your AWS access key YOUR_AWS_SECRET_ACCESS_KEY - Your AWS secret key YOUR_AWS_ACCOUNT_ID - Your 12-digit AWS account number YOUR_CONTACT_ID - FreeAgent contact ID for AWS YOUR_CATEGORY_ID - FreeAgent category for cloud services YOUR_BANK_ACCOUNT_ID - FreeAgent bank account for payments Credentials to Add PostgreSQL database credentials (3 nodes) FreeAgent OAuth2 credentials (2 nodes) Use Cases Freelancers & Consultants**: Automatically track AWS infrastructure costs Small Businesses**: Streamline bookkeeping for cloud expenses Agencies**: Manage multiple AWS accounts with separate workflows Accountants**: Reduce manual data entry for client AWS bills Database Schema The workflow uses a PostgreSQL table to track processed invoices - To initially create the table you need to run : CREATE TABLE aws_invoices_processed ( id SERIAL PRIMARY KEY, aws_invoice_id VARCHAR(255) UNIQUE NOT NULL, freeagent_invoice_url TEXT NOT NULL, billing_period VARCHAR(7) NOT NULL, amount DECIMAL(10, 2) NOT NULL, currency VARCHAR(3) NOT NULL, processed_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP ); Customization VAT Rate**: Default is 20% (UK), adjust in "Prepare FreeAgent Bill" node Schedule**: Modify cron expression in "Schedule Trigger" node Description Format**: Customize invoice description in code nodes Multi-Account**: Duplicate workflow for each AWS account Notes AWS dates are reversed: DueDate is earlier than IssuedDate, so the workflow swaps these All amounts are processed in the currency specified by AWS The "DELETE Test Record" node is disabled by default - use for testing only

How it works This workflow listens for new products in Shopify and transforms the product data into polished social media content. It generates captions and hashtags using an AI model, then posts the product to Instagram and Facebook using the Facebook Graph API. It logs every post to Google Sheets and sends a confirmation message to Discord. The flow ensures consistent publishing across all platforms with automated formatting and tracking. Step-by-step Trigger on Shopify product creation** Shopify Trigger – Activates when a new product is added to the store. Prepare product data** parse product data – Extracts product name, price, description, URL, image, and timestamp. Generate caption and hashtags** Generate caption and hashtags – Uses an AI model to craft a caption and produce 10 relevant hashtags. Configure posting parameters** Set Configuration – Stores access tokens, platform IDs, caption text, hashtags, and image URL. Publish to Instagram** Create Instagram Media Container – Sends the image and caption to create a media container. Wait for Processing – Waits for the container to finish processing. Publish Instagram Media – Publishes the processed container to the Instagram feed. Publish to Facebook** Download Image for Facebook – Downloads the product image from Shopify. Post to Facebook Page – Uploads the image with the caption and hashtags to the Facebook Page. Merge publishing results** Merge – Combines responses from Instagram and Facebook for unified logging. Log post to Google Sheets** Log Product Post Data – Appends product info, caption, and hashtags to a spreadsheet. Notify via Discord** Notify Discord About Post – Sends a message summarizing the published product. Why use this? Ensures every new Shopify product is promoted instantly across major social platforms. Eliminates manual posting and caption creation with reliable automation. Maintains centralized logging for auditing, tracking, or analytics. Provides real-time team notifications to confirm successful posts. Reduces errors and keeps brand messaging consistent across channels.

Who is this for This template is for sales teams, lead generation agencies, and growth marketers who want to build targeted lists of WooCommerce store owners -- complete with verified emails, phone numbers, and social profiles -- and have those contacts automatically land in Airtable for outreach or CRM workflows. How it works A manual trigger starts the workflow and a configuration node lets you set your target country, lead volume, and which data points to collect (emails, phones). A POST request to the ScraperCity store-leads API kicks off an async scrape job targeting WooCommerce stores and returns a runId. The workflow enters a polling loop -- waiting 60 seconds between each status check -- until the ScraperCity job reports SUCCEEDED. Once complete, the results CSV is downloaded via the ScraperCity download endpoint. A Code node parses the CSV, cleans the data, and deduplicates records by email address. A filter removes rows missing both email and phone, keeping only actionable contacts. Each verified contact is upserted into an Airtable base, ready for outreach. How to set up Create a ScraperCity account at scrapercity.com and copy your API key. In n8n, create an HTTP Header Auth credential named ScraperCity API Key with the header Authorization: Bearer YOUR_KEY. Create an Airtable personal access token credential in n8n. Open the Configure Scrape Parameters node and set your country code, lead volume, and Airtable base/table IDs. Click Execute workflow to run. Requirements ScraperCity account (store-leads product) Airtable account with a base containing columns: Name, Website, Email, Phone, Instagram, Facebook, Country n8n instance (cloud or self-hosted) How to customize the workflow Change platform in the config node from woocommerce to shopify to target Shopify stores instead. Adjust totalLeads to scrape more or fewer contacts per run. Add a Filter node after the Code node to restrict results to stores with Instagram profiles only. Replace the Airtable output node with HubSpot, Google Sheets, or Notion to match your CRM stack. Attach a Schedule Trigger to run the scrape weekly for ongoing lead generation.

🛠️ Pipedrive Tool MCP Server Complete MCP server exposing all Pipedrive Tool operations to AI agents. Zero configuration needed - all 45 operations pre-built. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community 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 🔧 How it Works • MCP Trigger: Serves as your server endpoint for AI agent requests • Tool Nodes: Pre-configured for every Pipedrive Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Pipedrive Tool tool with full error handling 📋 Available Operations (45 total) Every possible Pipedrive Tool operation is included: 🔧 Activity (5 operations) • Create an activity • Delete an activity • Get an activity • Get many activities • Update an activity 💰 Deal (7 operations) • Create a deal • Delete a deal • Duplicate a deal • Get a deal • Get many deals • Search a deal • Update a deal 🔧 Dealactivity (1 operations) • Get many deal activities 🔧 Dealproduct (4 operations) • Add a deal product • Get many deal products • Remove a deal product • Update a deal product 📄 File (5 operations) • Create a file • Delete a file • Download a file • Get a file • update details of a file 🔧 Lead (5 operations) • Create a lead • Delete a lead • Get a lead • Get many leads • Update a lead 🔧 Note (5 operations) • Create a note • Delete a note • Get a note • Get many notes • Update a note 🏢 Organization (6 operations) • Create an organization • Delete an organization • Get an organization • Get many organizations • Search an organization • Update an organization 👥 Person (6 operations) • Create a person • Delete a person • Get a person • Get many people • Search a person • Update a person 🔧 Product (1 operations) • Get many products 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Resource IDs and identifiers • Search queries and filters • Content and data payloads • Configuration options Response Format: Native Pipedrive Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • Other n8n Workflows: Call MCP tools from any workflow • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Complete Coverage: Every Pipedrive Tool operation available • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n error handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

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 23 AWS Budgets API operations to AI agents. ⚡ Quick Setup Import this workflow into your n8n instance Credentials Add AWS Budgets credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the AWS Budgets API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to https://budgets.amazonaws.com • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (23 total) 🔧 #X-Amz-Target=Awsbudgetservicegateway.Createbudget (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.CreateBudget: Creates a budget and, if included, notifications and subscribers. <important> Only one of BudgetLimit or PlannedBudgetLimits can be present in the syntax at one time. Use the syntax that matches your case. The Request Syntax section shows the BudgetLimit syntax. For PlannedBudgetLimits, see the Examples section. </important> 🔧 #X-Amz-Target=Awsbudgetservicegateway.Createbudgetaction (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.CreateBudgetAction: Creates a budget action. 🔧 #X-Amz-Target=Awsbudgetservicegateway.Createnotification (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.CreateNotification: Creates a notification. You must create the budget before you create the associated notification. 🔧 #X-Amz-Target=Awsbudgetservicegateway.Createsubscriber (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.CreateSubscriber: Creates a subscriber. You must create the associated budget and notification before you create the subscriber. 🔧 #X-Amz-Target=Awsbudgetservicegateway.Deletebudget (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.DeleteBudget: Deletes a budget. You can delete your budget at any time. <important> Deleting a budget also deletes the notifications and subscribers that are associated with that budget. </important> 🔧 #X-Amz-Target=Awsbudgetservicegateway.Deletebudgetaction (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.DeleteBudgetAction: Deletes a budget action. 🔧 #X-Amz-Target=Awsbudgetservicegateway.Deletenotification (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.DeleteNotification: Deletes a notification. <important> Deleting a notification also deletes the subscribers that are associated with the notification. </important> 🔧 #X-Amz-Target=Awsbudgetservicegateway.Deletesubscriber (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.DeleteSubscriber: Deletes a subscriber. <important> Deleting the last subscriber to a notification also deletes the notification. </important> 🔧 #X-Amz-Target=Awsbudgetservicegateway.Describebudget (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.DescribeBudget: Describes a budget. <important> The Request Syntax section shows the BudgetLimit syntax. For PlannedBudgetLimits, see the Examples section. </important> 🔧 #X-Amz-Target=Awsbudgetservicegateway.Describebudgetaction (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.DescribeBudgetAction: Describes a budget action detail. 🔧 #X-Amz-Target=Awsbudgetservicegateway.Describebudgetactionhistories (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.DescribeBudgetActionHistories: Describes a budget action history detail. 🔧 #X-Amz-Target=Awsbudgetservicegateway.Describebudgetactionsforaccount (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.DescribeBudgetActionsForAccount: Describes all of the budget actions for an account. 🔧 #X-Amz-Target=Awsbudgetservicegateway.Describebudgetactionsforbudget (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.DescribeBudgetActionsForBudget: Describes all of the budget actions for a budget. 🔧 #X-Amz-Target=Awsbudgetservicegateway.Describebudgetnotificationsforaccount (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.DescribeBudgetNotificationsForAccount: Lists the budget names and notifications that are associated with an account. 🔧 #X-Amz-Target=Awsbudgetservicegateway.Describebudgetperformancehistory (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.DescribeBudgetPerformanceHistory: Describes the history for DAILY, MONTHLY, and QUARTERLY budgets. Budget history isn't available for ANNUAL budgets. 🔧 #X-Amz-Target=Awsbudgetservicegateway.Describebudgets (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.DescribeBudgets: Lists the budgets that are associated with an account. <important> The Request Syntax section shows the BudgetLimit syntax. For PlannedBudgetLimits, see the Examples section. </important> 🔧 #X-Amz-Target=Awsbudgetservicegateway.Describenotificationsforbudget (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.DescribeNotificationsForBudget: Lists the notifications that are associated with a budget. 🔧 #X-Amz-Target=Awsbudgetservicegateway.Describesubscribersfornotification (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.DescribeSubscribersForNotification: Lists the subscribers that are associated with a notification. 🔧 #X-Amz-Target=Awsbudgetservicegateway.Executebudgetaction (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.ExecuteBudgetAction: Executes a budget action. 🔧 #X-Amz-Target=Awsbudgetservicegateway.Updatebudget (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.UpdateBudget: Updates a budget. You can change every part of a budget except for the budgetName and the calculatedSpend. When you modify a budget, the calculatedSpend drops to zero until Amazon Web Services has new usage data to use for forecasting. <important> Only one of BudgetLimit or PlannedBudgetLimits can be present in the syntax at one time. Use the syntax that matches your case. The Request Syntax section shows the BudgetLimit syntax. For PlannedBudgetLimits, see the Examples section. </important> 🔧 #X-Amz-Target=Awsbudgetservicegateway.Updatebudgetaction (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.UpdateBudgetAction: Updates a budget action. 🔧 #X-Amz-Target=Awsbudgetservicegateway.Updatenotification (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.UpdateNotification: Updates a notification. 🔧 #X-Amz-Target=Awsbudgetservicegateway.Updatesubscriber (1 endpoints) • POST /#X-Amz-Target=AWSBudgetServiceGateway.UpdateSubscriber: Updates a subscriber. 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native AWS Budgets API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

Complete MCP server exposing 21 api.clarify.io API operations to AI agents. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Credentials Add api.clarify.io credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the api.clarify.io API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to https://api.clarify.io/ • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (21 total) 🔧 V1 (21 endpoints) • GET /v1/bundles: Add Media to Track • POST /v1/bundles: Create a bundle • DELETE /v1/bundles/{bundle_id}: Delete a bundle • GET /v1/bundles/{bundle_id}: Get a bundle • PUT /v1/bundles/{bundle_id}: Update a bundle • GET /v1/bundles/{bundle_id}/insights: Get bundle insights • POST /v1/bundles/{bundle_id}/insights: Request an insight to be run • GET /v1/bundles/{bundle_id}/insights/{insight_id}: Get bundle insight • DELETE /v1/bundles/{bundle_id}/metadata: Delete bundle metadata • GET /v1/bundles/{bundle_id}/metadata: Get bundle metadata • PUT /v1/bundles/{bundle_id}/metadata: Update bundle metadata • DELETE /v1/bundles/{bundle_id}/tracks: Delete bundle tracks • GET /v1/bundles/{bundle_id}/tracks: Get bundle tracks • POST /v1/bundles/{bundle_id}/tracks: Add a track for a bundle • PUT /v1/bundles/{bundle_id}/tracks: Update a tracks for a bundle • DELETE /v1/bundles/{bundle_id}/tracks/{track_id}: Delete a bundle track • GET /v1/bundles/{bundle_id}/tracks/{track_id}: Get bundle track • PUT /v1/bundles/{bundle_id}/tracks/{track_id}: Add media to a track • GET /v1/reports/scores: Generate Group Report • GET /v1/reports/trends: Generate Trends Report • GET /v1/search: Search Bundles 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native api.clarify.io API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

Complete MCP server exposing 18 Bufferapp API operations to AI agents. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Credentials Add Bufferapp credentials Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works This workflow converts the Bufferapp API into an MCP-compatible interface for AI agents. • MCP Trigger: Serves as your server endpoint for AI agent requests • HTTP Request Nodes: Handle API calls to https://api.bufferapp.com/1/ • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Returns responses directly to the AI agent 📋 Available Operations (18 total) 🔧 Info (1 endpoints) • GET /info/configuration{mediaTypeExtension}: Get Configuration 🔧 Links (1 endpoints) • GET /links/shares{mediaTypeExtension}: Get Link Shares 🔧 Profiles (7 endpoints) • POST /profiles/{id}/schedules/update{mediaTypeExtension}: Update Profile Schedules • GET /profiles/{id}/schedules{mediaTypeExtension}: Get Profile Schedules • GET /profiles/{id}/updates/pending{mediaTypeExtension}: Get Pending Updates • POST /profiles/{id}/updates/reorder{mediaTypeExtension}: Reorder Profile Updates • GET /profiles/{id}/updates/sent{mediaTypeExtension}: Get Sent Updates • POST /profiles/{id}/updates/shuffle{mediaTypeExtension}: Shuffle Profile Updates • GET /profiles/{id}{mediaTypeExtension}: Get Profile Details 🔧 Profiles{Mediatypeextension} (1 endpoints) • GET /profiles{mediaTypeExtension}: List Profiles 🔧 Updates (7 endpoints) • POST /updates/create{mediaTypeExtension}: Create Status Update • POST /updates/{id}/destroy{mediaTypeExtension}: Delete Status Update • GET /updates/{id}/interactions{mediaTypeExtension}: Get Update Interactions • POST /updates/{id}/move_to_top{mediaTypeExtension}: Move Update to Top • POST /updates/{id}/share{mediaTypeExtension}: Share Update Now • POST /updates/{id}/update{mediaTypeExtension}: Edit Status Update • GET /updates/{id}{mediaTypeExtension}: Get Update Details 🔧 User{Mediatypeextension} (1 endpoints) • GET /user{mediaTypeExtension}: Get User Details 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Path parameters and identifiers • Query parameters and filters • Request body data • Headers and authentication Response Format: Native Bufferapp API responses with full data structure Error Handling: Built-in n8n HTTP request error management 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Cursor: Add MCP server SSE URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n HTTP request handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

How It Works This workflow automates social media content creation and posting. It starts by receiving raw text input through a Webhook (for example, from LINE Bot) and saves the content into a Notion database for centralized storage. Next, GPT-4 generates platform-specific captions for Instagram, Threads, X/Twitter, and Blog. Instagram captions are prepared for automatic publishing, while Threads, X, and Blog drafts are stored in Notion for later review and manual posting. The workflow then fetches book cover images or other visuals from external APIs such as Google Books, OpenBD, or OpenLibrary. The chosen image is uploaded to Cloudinary to generate a secure, optimized URL. Finally, the Instagram Graph API is used to create a media container and publish the post automatically with the caption and image. This way, the workflow provides both automation for Instagram and reusable drafts for other platforms. Requirements Notion account with a database configured for text and captions Cloudinary account for image hosting Instagram Business account connected to the Meta Developer Platform GPT-4 (via OpenAI or LangChain node in n8n) Setup Instructions Configure the Webhook node to capture text input. Update the Notion database ID and property keys to match your schema. Add Cloudinary credentials (【cloud_name】, 【upload_preset】) in the HTTP Request node. Set 【IG_ACCESS_TOKEN】 as an environment variable. Activate the workflow and test with a sample input. Customization Adjust caption prompts for style, hashtags, or character limits. Add additional GPT nodes for more platforms. Replace or extend image sources as needed. Integrate a scheduler (Cron node) to post at specific times.

Description Automates the forwarding of messages from WhatsApp (via Evolution API) to Chatwoot, enabling seamless integration between external WhatsApp users and internal Chatwoot agents. It supports both text and media messages, ensuring that customer conversations are centralized and accessible for support teams. What Problem Does This Solve? Managing conversations across multiple platforms can lead to fragmented support and lost context. This subworkflow bridges the gap between WhatsApp and Chatwoot, automatically forwarding messages received via the Evolution API to a Chatwoot inbox. It simplifies communication flow, centralizes conversations, and enhances the support team's productivity. Features Support for plain text messages Support for media messages: images, videos, documents, and audio Automatic media upload to Chatwoot with proper attachment rendering Automatic contact association using WhatsApp number and Chatwoot API Designed to work with Evolution API webhooks or any message source Prerequisites Before using this automate, make sure you have: Evolution API credentials with incoming message webhook configured A Chatwoot instance with access token and API endpoint An existing Chatwoot inbox (preferably API channel) A configured HTTP Request node in n8n for Chatwoot API calls Suggested Usage This subworkflow should be attached to a parent workflow that receives WhatsApp messages via the Evolution API webhook. Ideal for: Centralized customer service operations WhatsApp-to-CRM/chat routing Hybrid automation workflows where human agents need to reply from Chatwoot It ensures that all incoming WhatsApp messages are properly converted and forwarded to Chatwoot, preserving message content and structure.

Multi-Source RAG System with GPT-4 Turbo, News & Academic Papers Integration This workflow provides an enterprise-grade RAG (Retrieval-Augmented Generation) system that intelligently searches multiple sources and generates AI-powered responses using GPT-4 Turbo. How it works This workflow provides an enterprise-grade RAG (Retrieval-Augmented Generation) system that intelligently searches multiple sources and generates AI-powered responses using GPT-4 Turbo. Key Steps Form Input - Collects user queries with customizable search scope, response style, and language preferences Intelligent Search - Routes queries to appropriate sources (web, academic papers, news, internal documents) Data Aggregation - Unifies and processes information from multiple sources with quality scoring AI Processing - Uses GPT-4 Turbo to generate context-aware, source-grounded responses Response Enhancement - Formats outputs in various styles (comprehensive, concise, technical, etc.) Multi-Channel Delivery - Delivers results via webhook, email, Slack, and optional PDF generation Data Sources & AI Models Search Sources Web Search**: Google, Bing, DuckDuckGo integration Academic Papers**: arXiv, PubMed, Google Scholar News Articles**: News API, RSS feeds, real-time news Technical Documentation**: GitHub, Stack Overflow, documentation sites Internal Knowledge**: Google Drive, Confluence, Notion integration AI Models GPT-4 Turbo**: Primary language model for response generation Embedding Models**: For semantic search and similarity matching Custom Prompts**: Specialized prompts for different response styles Set up steps Setup time: 15-20 minutes Configure API credentials - Set up OpenAI API, ScrapeGraphAI, Google Drive, and other service credentials Set up search sources - Configure academic databases, news APIs, and internal knowledge sources Connect analytics - Link Google Sheets for usage tracking and performance monitoring Configure notifications - Set up Slack channels and email templates for automated alerts Test the workflow - Run sample queries to verify all components are working correctly Keep detailed configuration notes in sticky notes inside your workflow

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How it works This workflow automatically monitors trending topics across multiple platforms and generates content strategy insights for marketing teams. Key Steps Daily Trigger - Runs automatically every 24 hours to capture fresh trends and viral content. Multi-Platform Scraping - Uses AI-powered scrapers to analyze trends from LinkedIn, Twitter, Instagram, Google Trends, BuzzSumo, and Reddit. Trend Analysis - Processes collected data to identify viral patterns, engagement metrics, and content opportunities. Content Strategy Generation - Creates actionable insights for content planning and social media strategy. Team Notifications - Sends comprehensive reports to Slack and updates content calendars in Google Sheets. Set up steps Setup time: 10-15 minutes Configure ScrapeGraphAI credentials - Add your ScrapeGraphAI API key for AI-powered trend scraping. Set up Slack connection - Connect your Slack workspace for team notifications. Configure Google Sheets - Set up a Google Sheets connection for content calendar updates. Customize target industries - Modify the configuration to focus on your specific industry verticals (AI, marketing, tech, etc.). Adjust monitoring frequency - Change the trigger timing based on your content planning needs. What you get Daily trend reports** with viral content analysis and engagement metrics Content opportunity scores** for different platforms and topics Automated content calendar updates** with trending topics and suggested content Team notifications** with key insights and actionable recommendations Competitive analysis** of viral content patterns and successful strategies