Generate SEO seed keywords using AI

Analyze cryptocurrency market data with HTX API, GPT-4o and Telegram

A fully autonomous, HTX Spot Market AI Agent (Huobi AI Agent) built using GPT-4o and Telegram. This workflow is the primary interface, orchestrating all internal reasoning, trading logic, and output formatting. --- ⚙️ Core Features 🧠 LLM-Powered Intelligence: Built on GPT-4o with advanced reasoning ⏱️ Multi-Timeframe Support: 15m, 1h, 4h, and 1d indicator logic 🧩 Self-Contained Multi-Agent Workflow: No external subflows required 🧮 Real-Time HTX Market Dat

Transform text data into structured format and add it to Google Sheets using a custom webhook

Automatically convert unstructured text into structured data and add it to Google Sheets using a custom webhook and ChatGPT.

Fetch dataset items from Apify and create a completion with ChatGPT, then add a row to Google Sheets

Automatically fetch dataset items from Apify, generate a completion with ChatGPT, and add the results to Google Sheets for streamlined data management.

Send replies to messages using OpenAI GPT-3 and watch for new messages in Line

Automatically respond to incoming Line messages using ChatGPT. Monitor new messages and send intelligent replies directly through Line.

🎙️ VoiceFlow AI: Telegram + Deepgram + OpenAI + Supabase audio assistant

AI Audio Assistant with Voice-to-Voice Response Who is this for? Businesses, customer service teams, content creators, and organizations who want to provide intelligent voice-based interactions through Telegram. Perfect for accessibility-focused services, multilingual support, or hands-free customer assistance. What problem does this solve? - Enables natural voice conversations with AI - Breaks down language and accessibility barriers - Provides instant voice responses to custome

Monitor new YouTube comments and reply using ChatGPT

Use this template to monitor new YouTube comments and reply using ChatGPT. Enhance engagement by responding to comments with AI-generated replies.

Build a company website RAG chatbot using Apify, Pinecone and Gemini

AI chatbots are only as good as the data they learn from. Most large language models (LLM) rely only on their training datasets. If you want the chatbots to know more about your business, the best is to implement a retrieval-augmented generation (RAG) pipeline to train Gemini with your website data. This is what this workflow will help you to do. This workflow uses a scheduler to scrape a website on a regular basis using Apify; web pages are then indexed or updated in a Pinecone vector database.

Build an MCP server with Google Calendar and custom functions

Learn how to build an MCP Server and Client in n8n with official nodes. > ⚠ Requires n8n version 1.88.0 or higher. In this example, we use Google Calendar and custom functions as two separate MCP Servers, demonstrating how to integrate both native and custom tools. How it works The AI Agent connects to two MCP Servers. Each MCP Trigger (Server) generates a URL exposing its tools. This URL is used by an MCP Client linked to the AI Agent. Whenever you make changes to the tools, there’s