Rohit Dabra
As the CTO of QServices, I lead digital transformation for startups and SMBs by building scalable, AI-powered SaaS solutions that solve real-world business challenges.
Templates by Rohit Dabra
Manage Odoo CRM with natural language using OpenAI and MCP Server
Odoo CRM MCP Server Workflow 📖 Overview This workflow connects an AI Agent with Odoo CRM using the Model Context Protocol (MCP). It allows users to manage CRM data in Odoo through natural language chat commands. The assistant interprets the user’s request, selects the appropriate Odoo action, and executes it seamlessly. 🔹 Key Features Contacts Management: Create, update, delete, and retrieve contacts. Opportunities Management: Create, update, delete, and retrieve opportunities. Notes Management: Create, update, delete, and retrieve notes. Conversational AI Agent: Understands natural language and maps requests to Odoo actions. Model Used: OpenAI Chat Model. This makes it easy for end-users to interact with Odoo CRM without needing technical commands—just plain language instructions. --- ▶️ Demo Video Watch the full demo here: 👉 YouTube Demo Video --- ⚙️ Setup Guide Follow these steps to set up and run the workflow: Prerequisites An Odoo instance configured with CRM enabled. An n8n or automation platform account where MCP workflows are supported. An OpenAI API key with access to GPT models. MCP Server installed and running. Import the Workflow Download the provided workflow JSON file. In your automation platform (n8n, Langflow, or other MCP-enabled tool), choose Import Workflow. Select the JSON file and confirm. Configure MCP Server Go to your MCP Server Trigger node in the workflow. Configure it to connect with your Odoo instance. Set API endpoint. Provide authentication credentials (API key). Test the connection to ensure the MCP server can reach Odoo. Configure the OpenAI Model Select the OpenAI Chat Model node in the workflow. Enter your OpenAI API Key. Choose the model (e.g., gpt-5 or gpt-5-mini). AI Agent Setup The AI Agent node links the Chat Model, Memory, and MCP Client. Ensure the MCP Client is mapped to the correct Odoo tools (Contacts, Opportunities, Notes). The System Prompt defines assistant behavior—use the tailored system prompt provided earlier. Activate and Test Turn the workflow ON (toggle Active). Open chat and type: "Create a contact named John Doe with email john@example.com." "Show me all opportunities." "Add a note to John Doe saying 'Follow-up scheduled for Friday'." Verify the results in your Odoo CRM. --- ✅ Next Steps Extend functionality with Tasks, Stages, Companies, and Communication Logs for a complete CRM experience. Add confirmation prompts for destructive actions (delete contact/opportunity/note). Customize the AI Agent’s system prompt for your organization’s workflows. ---
By Rohit DabraJira project management automation with Google Gemini & MCP server
Jira MCP Server Integration with n8n Overview Transform your Jira project management with the power of AI and automation! This n8n workflow template demonstrates how to create a seamless integration between chat interfaces, AI processing, and Jira Software using MCP (Model Context Protocol) server architecture. What This Workflow Does Chat-Driven Automation: Trigger Jira operations through simple chat messages AI-Powered Issue Creation: Automatically generate detailed Jira issues with descriptions and acceptance criteria Complete Jira Management: Get issue status, changelogs, comments, and perform full CRUD operations Memory Integration: Maintain context across conversations for smarter automations Zero Manual Entry: Eliminate repetitive data entry and human errors Key Features ✅ Natural Language Processing: Use Google Gemini to understand and process chat requests ✅ MCP Server Integration: Secure, efficient communication with Jira APIs ✅ Comprehensive Jira Operations: Create, read, update, delete issues and comments ✅ Smart Memory: Context-aware conversations for better automation ✅ Multi-Action Workflow: Handle multiple Jira operations from a single trigger Demo Video 🎥 Watch the Complete Demo: Automate Jira Issue Creation with n8n & AI | MCP Server Integration Prerequisites Before setting up this workflow, ensure you have: n8n instance (cloud or self-hosted) Jira Software account with appropriate permissions Google Gemini API credentials MCP Server configured and accessible Basic understanding of n8n workflows Setup Guide Step 1: Import the Workflow Copy the workflow JSON from this template In your n8n instance, click Import > From Text Paste the JSON and click Import Step 2: Configure Google Gemini Open the Google Gemini Chat Model node Add your Google Gemini API credentials Configure the model parameters: Model: gemini-pro (recommended) Temperature: 0.7 for balanced creativity Max tokens: As per your requirements Step 3: Set Up MCP Server Connection Configure the MCP Client node: Server URL: Your MCP server endpoint Authentication: Add required credentials Timeout: Set appropriate timeout values Ensure your MCP server supports Jira operations: Issue creation and retrieval Comment management Status updates Changelog access Step 4: Configure Jira Integration Set up Jira credentials in n8n: Go to Credentials > Add Credential Select Jira Software API Add your Jira instance URL, email, and API token Configure each Jira node: Get Issue Status: Set project key and filters Create Issue: Define issue type and required fields Manage Comments: Set permissions and content rules Step 5: Memory Configuration Configure the Simple Memory node: Set memory key for conversation context Define memory retention duration Configure memory scope (user/session level) Step 6: Chat Trigger Setup Configure the When Chat Message Received trigger: Set up webhook URL or chat platform integration Define message filters if needed Test the trigger with sample messages Usage Examples Creating a Jira Issue Chat Input: Can you create an issue in Jira for Login Page with detailed description and acceptance criteria? Expected Output: New Jira issue created with structured description Automatically generated acceptance criteria Proper labeling and categorization Getting Issue Status Chat Input: What's the status of issue PROJ-123? Expected Output: Current issue status Last updated information Assigned user details Managing Comments Chat Input: Add a comment to issue PROJ-123: "Ready for testing in staging environment" Expected Output: Comment added to specified issue Notification sent to relevant team members Customization Options Extending Jira Operations Add more Jira operations (transitions, watchers, attachments) Implement custom field handling Create multi-project workflows AI Enhancement Fine-tune Gemini prompts for better issue descriptions Add custom validation rules Implement approval workflows Integration Expansion Connect to Slack, Discord, or Teams Add email notifications Integrate with time tracking tools Troubleshooting Common Issues MCP Server Connection Failed Verify server URL and credentials Check network connectivity Ensure MCP server is running and accessible Jira API Errors Validate Jira credentials and permissions Check project access rights Verify issue type and field configurations AI Response Issues Review Gemini API quotas and limits Adjust prompt engineering for better results Check model parameters and settings Performance Tips Optimize memory usage for long conversations Implement rate limiting for API calls Use error handling and retry mechanisms Monitor workflow execution times Best Practices Security: Store all credentials securely using n8n's credential system Testing: Test each node individually before running the complete workflow Monitoring: Set up alerts for workflow failures and API limits Documentation: Keep track of custom configurations and modifications Backup: Regular backup of workflow configurations and credentials Happy Automating! 🚀 This workflow template is designed to boost productivity and eliminate manual Jira management tasks. Customize it according to your team's specific needs and processes.
By Rohit DabraManage WooCommerce store with natural language using GPT-4.1 and MCP server
WooCommerce AI Agent — n8n Workflow (Overview) Description: Turn your WooCommerce store into a conversational AI assistant — create products, place orders, run reports and manage coupons using natural language via n8n + an MCP Server. Key features Natural-language commands mapped to WooCommerce actions (products, orders, reports, coupons). Structured JSON outputs + lightweight mapping to avoid schema errors. Calls routed through your MCP Server for secure, auditable tool execution. Minimal user prompts — agent auto-fetches context and asks only when necessary. Extensible: add new tools or customize prompts/mappings easily. Demo of the workflow: Youtube Video 🚀 Setup Guide: WooCommerce + AI Agent Workflow in n8n Prerequisites Running n8n instance WooCommerce store with REST API keys OpenAI API key MCP server (production URL) --- Import Workflow Open n8n dashboard Go to Workflows → Import Upload/paste the workflow JSON Save as WooCommerce AI Agent --- Configure Credentials OpenAI Create new credential → OpenAI API Add your API key → Save & test WooCommerce Create new credential → WooCommerce API Enter Base URL, Consumer Key & Secret → Save & test MCP Client In MCP Client node, set Server URL to your MCP server production URL Add authentication if required --- Test Workflow Open workflow in editor Run a sample request (e.g., create a test product) Verify product appears in WooCommerce --- Activate Workflow Once tested, click Activate in n8n Workflow is now live 🎉 --- Troubleshooting Schema errors → Ensure fields match WooCommerce node requirements Connection issues → Re-check credentials and MCP URL
By Rohit DabraAutomate client invoicing & payments with Stripe, Google Sheets, Drive and Gmail
Google Sheets → Stripe Payment Automation Workflow 📌 Overview This workflow automates the end-to-end process of generating and sending client payment links using Google Sheets and Stripe. Whenever a new or updated entry is added to the Google Sheet, the workflow will: Fetch client and invoice details. Create a Stripe Product and Price. Generate a Stripe Payment Link. Store the link back in the Google Sheet. Upload a copy of the invoice to Google Drive. Send a professional, formatted email with the payment link to the client using Gmail. 🔗 Demo Video: Watch on YouTube --- ⚡️ Workflow Steps Trigger – The workflow is triggered on any update in the Google Sheet. Filter – Ensures only relevant rows (e.g., PENDING invoices) proceed. Stripe Automation Create Stripe Product Create Stripe Price Generate Stripe Payment Link Google Drive – Store invoice files (if required). Google Sheets – Update the sheet with the generated Stripe Payment Link and timestamp. Gmail – Send a client-facing email with the invoice details and payment link. --- 🛠 Setup Guide Prerequisites n8n account Google Sheets & Google Drive credentials Gmail API credentials Stripe API Key Steps Clone/Import Workflow Import the workflow JSON file into your n8n instance. Configure Google Sheets Create a Google Sheet with columns: Order ID, Client Name, Client Email, Items Description, Due Date, Amount, Currency, Invoice Status, Invoice Link, Stripe Payment Link, Last Updated Connect your Google Sheets node to this sheet. Set Up Stripe Obtain your Stripe Secret Key from Stripe Dashboard. Add it in the Stripe nodes for Product, Price, and Payment Link creation. Google Drive Configure to store invoice backups (optional). Gmail Authorize Gmail and set up the Send Email node. Customize the email template with client details and the Stripe link. Test the Workflow Add a sample row in Google Sheets. Run the workflow manually or update the sheet to trigger automatically. Verify that the Stripe link is created, updated in the sheet, and emailed to the client. --- ✅ Now your workflow is ready to automatically manage client invoices and payments with Stripe + Google Sheets + Gmail + Google Drive.
By Rohit Dabra