AI Workflows
Artificial Intelligence tools and workflows
AI-Powered Credit Card Recommendation System with OpenAI GPT, Telegram & Google Sheets
Overview Confused about which credit card to actually get or swipe? With 100+ cards on the market, hidden caps, and milestone rules, most people end up leaving rewards, perks, and cashback on the table. This workflow uses n8n + GPT + Google Sheets + Telegram to recommend the best credit card for each user's lifestyle in under 3 seconds, while keeping the logic transparent with a value breakdown. What does this workflow do? This workflow: - Captures User Inputs - Users answer a 7-question lifestyle quiz via Telegram. - Stores Responses - Google Sheets logs all answers for resumption & deduplication. - Scores Answers - n8n Function nodes map single & multi-select inputs into scores. - Generates Recommendations - GPT analyses profile vs. 30+ card dataset. - Breaks Down Value - Outputs a transparent table of rewards, milestones, lounge value. - Delivers Results - Top 3 card picks returned instantly on Telegram. Why is this useful? Most card comparison tools only list features; they don't personalize or calculate actual value. This workflow builds a decision engine: - Personalized – matches lifestyle to best-fit cards - Transparent – shows value in real currency (rewards, milestones, lounges) - Fast – answers in under 3 seconds - Organized – Google Sheets keeps an audit trail of every user + dedupe Tools used - n8n (Orchestrator): Orchestration + logic branching - Telegram: User-facing quiz bot - Google Sheets: Database of credit cards + logs of user answers - OpenAI (GPT): Analyses user profile & generates recommendations Who is this for? - Fintech product builders – see how AI can power recommendation engines - Cardholders – understand which card fits their lifestyle best - n8n makers – learn how to combine Sheets + GPT + chat interface into one workflow How to adapt it for your country/location This workflow uses a credit card dataset stored in Google Sheets. To make it work for your country: - Build your dataset – scrape or collect card details from banks, comparison sites, or official portals - Fields to include: Fees, Reward rate, Lounge access, Forex markup, Reward caps, Milestones, Eligibility. - You can use web crawlers (e.g., Apify, PhantomBuster) to automate data collection. - Update the Google Sheet – replace the India dataset with your country's cards. - Adjust scoring logic – modify Function nodes if your cards use different reward structures (e.g., cashback %, miles, points value). - Run the workflow – GPT will analyse against the new dataset and generate recommendations specific to your country. This makes the workflow flexible for any geography. Workflow Highlights - End-to-end credit card recommendation pipeline (quiz → scoring → GPT → result) - Handles single + multi-select inputs fairly with % match scoring - Transparent value breakdown in local currency (rewards, milestones, lounge access) - Google Sheets for persistence, dedupe & audit trail - Delivers top 3 cards in <3 seconds on Telegram - Fully customizable for any country by swapping the dataset
n8n$24.99Automate YouTube Video Repurposing into Diverse Content Formats with AI and Airtable
This workflow enables content creators to automatically transform YouTube videos into various content formats using AI and Airtable, maximizing content reach and efficiency.
n8n$19.99Create Personal Data Vector Store from Google Sheets with OpenAI & Gemini AI
This workflow integrates **Google Sheets** with **Supabase Vector Store** for storing personal data as vectors. It utilizes **OpenAI** and **Google Gemini** AI models for enhanced data processing and querying. The workflow performs the following tasks: - **Extracts personal data** from Google Sheets. - Processes the data using **AI tools** like OpenAI and Google Gemini for intelligent insights. - **Inserts the data** into **Supabase** as vectors, enabling efficient storage and fast querying. - Includes seamless integration with **Postgres** for memory management. - Supports data **loading**, **embedding**, and **management**. This template is ideal for: - Personal data storage with AI-driven **querying** and **analysis**. - Building **intelligent agents** that interact with your data. - Efficient vector-based storage for **personal information**. Perfect for those looking to integrate AI into their personal data workflows.
n8n$9.99Multi-Service Task Automation with AI-Powered Agent System via WhatsApp
Think of this workflow as your very own **J.A.R.V.I.S.**, the ultimate AI personal assistant, capable of handling a vast array of tasks just like Tony Stark's legendary AI! --- ### Overview This n8n workflow creates a **highly intelligent, multi-agent AI system** designed to act as your all-in-one personal assistant. At its core is **Jarvis**, the central AI, who smartly understands your requests and delegates them to specialized supervisor AIs. These supervisors then activate their own sub-agents (smaller AI workflows) to perform specific tasks, covering everything from managing your work to helping with your personal life and getting you the information you need. --- ### Use Case This powerful workflow is perfect for anyone who wants to **automate and streamline almost any digital task**. Imagine having an assistant who can: * **Boost Productivity:** Manage your calendar, create and update documents (Google Docs, Sheets, Drive), handle tasks (ClickUp, Google Tasks), and keep your customer data organized (Zoho CRM, Airtable). * **Master Communication:** Draft and search emails, send messages on Slack, and even manage your Twitter interactions. * **Handle Publishing & Content:** Create images, post on social media (Facebook, Twitter, LinkedIn, Instagram), and manage your WordPress content. * **Provide Smart Insights:** Perform deep online research, analyze SEO trends, check financial markets, and gather website performance data from Google Analytics. * **Manage Your Lifestyle:** Keep track of your meal plans and habits in Notion, and even help you with travel planning. This system is designed to intelligently choose the best tool for each part of your request, making complex tasks simple. --- ### How It Works It all starts with your input, delivered via **WhatsApp**. Whether you send a text message, an audio note (which gets transcribed), an image, or a document (from which data like invoices can be extracted), the workflow processes it to understand your need. This input then goes to **Jarvis, the central AI**. Jarvis acts like a super-smart manager. It quickly figures out which supervisor agent is best for your request: * **Productivity Supervisor:** For anything work-related - documents, calendars, tasks, or CRM. * **Communication Supervisor:** For emails, Slack, or Twitter. * **Lifestyle Supervisor:** For personal organization like meals or travel. * **Insights Supervisor:** For research, SEO, financial data, or website analytics. * **Publishing Supervisor:** For social media posting, images, or WordPress. Jarvis then hands off your request to the chosen supervisor. Each supervisor, in turn, uses its own set of specialized sub-agents (individual n8n workflows) to get the job done. For example, if you ask Jarvis to find me flight information, it directs it to the Lifestyle Supervisor, which then uses the Travel Agent to look up flights. The results are then sent back to you directly through WhatsApp. This Agent as a Tool setup means complex tasks are broken down and handled by the right expert AI. --- ### How to Set It Up 1. **Individual Agent Workflows:** This system is built with many specialized AI agents working together. To get started, you'll need to set up a separate n8n workflow for *each* of the individual agents (like Notion Agent, Email Agent, SEO Agent, etc.). 2. **Connect Agents:** Once created, these individual agent workflows must be correctly linked to their designated call workflow tools within the main supervisor workflows. This tells Jarvis and its supervisors which tools to use for each task. 3. **Credentials:** Make sure you've properly connected all necessary accounts and API keys (like Google, OpenAI, Slack, Airtable, etc.) within their respective agent workflows. 4. **Activate:** After setting up and linking all parts and adding your credentials, activate this main workflow. For more detailed setup instructions, please refer to our [**Detailed Setup Guide**](https://drive.google.com/file/d/1UqQpZv5ExuI5IEIUMe6NiZ89bVCI9J/view?usp=sharing). If you need any further help, don't hesitate to email us at `info.gainflow@gmail.com`.
n8n$24.99Create a Custom Conversational AI Agent with LangChain and Google Gemini
Develop a personalized AI conversational agent using LangChain and Google Gemini for self-hosted environments, offering extensive customization and efficient token usage.
n8n$9.99Voice-Activated AI Responses with Siri and Apple Shortcuts
Leverage Siri and Apple Shortcuts to trigger AI-driven responses using n8n. Customize inputs and outputs for a seamless voice-activated experience.
n8n$4.99AI-Powered Chatbot Workflow with MySQL Database Integration
# AI-Powered Chatbot Workflow with MySQL Integration This guide shows you how to deploy a chatbot that lets you query your database using natural language. You will build a system that accepts chat messages, retains conversation history, constructs dynamic SQL queries, and returns responses generated by an AI model. By following these instructions, you will have a working solution that integrates n8n's AI Agent capabilities with MySQL. --- ## Prerequisites Before you begin, ensure that you have the following: 1. An active n8n instance (self-hosted or cloud) running version 1.50.0 or later. 2. Valid MySQL credentials configured in n8n. 3. API credentials for the Groq Chat Model (or your preferred AI language model). 4. Basic familiarity with SQL and n8n node concepts such as chat triggers and memory buffers. 5. Access to the [n8n Docs on AI Agents](https://docs.n8n.io/advanced-ai/) for further reference. --- ## Workflow Setup ### 1. Chat Interface & Trigger - **When Chat Message Received**: This node listens for incoming chat messages via a webhook. When a message arrives, it triggers the workflow immediately. ### 2. Conversation Memory - **Chat History**: This memory buffer node stores the last 10 interactions. It supplies conversation context to the AI Agent, ensuring that responses consider previous messages. ### 3. AI Agent Core - **AI Agent (Tools Agent)**: The AI Agent node orchestrates the conversation by receiving the chat input and conversation history. It dynamically generates SQL queries based on your requests and coordinates calls to external tools (such as MySQL nodes). ### 4. Database Interactions - **MySQL Node**: This node executes the SQL query generated by the AI Agent. You reference the query using an expression (e.g., `{{$node["AI Agent"].json["sql_query"]}}`), allowing the agent's output to control data retrieval. - **MySQL Schema Node**: This node retrieves a list of base tables from your MySQL database (excluding system schemas). The agent uses this information to understand the available tables. - **MySQL Definition Node**: This node fetches detailed metadata (such as column names, data types, and relationships) for a specific table. The table and schema names are supplied dynamically by the AI Agent. ### 5. Language Model Processing - **Groq Chat Model**: This node connects to the Groq Chat API to generate text completions. It processes the combined input (chat message, context, and data fetched from MySQL) and produces the final response. ### 6. Guidance & Customization - **Sticky Notes**: These nodes provide guidance on: - Switching the chat model if you wish to use another provider (e.g., OpenAI or Anthropic). - Adjusting the maximum token count per interaction. - Customizing the SQL queries and the context window size. They help you modify the workflow to suit your environment and requirements. ### Workflow Connections - The **Chat Trigger** passes the incoming message to the **AI Agent**. - The **Chat History** node supplies conversation context to the AI Agent. - The **AI Agent** calls the MySQL nodes as external tools, generating and sending dynamic SQL queries. - The **Groq Chat Model** processes the consolidated input from the agent and outputs the natural language response delivered to the user. ### Testing the Workflow 1. Send a chat message using the chat interface. 2. Observe how the AI Agent processes the input and generates a corresponding SQL query. 3. Verify that the MySQL nodes execute the query and return data. 4. Confirm that the Groq Chat Model produces a coherent natural language response. 5. Refer to the sticky notes for guidance if you need to fine-tune any node settings. --- ## Next Steps and References - **Customize Your AI Model**: Replace the Groq Chat Model with another language model (such as the OpenAI Chat Model) by updating the node credentials and configuration. - **Enhance Memory Settings**: Adjust the Chat History node's context window to retain more or fewer messages based on your needs. - **Modify SQL Queries**: Update the SQL queries in the MySQL nodes to match your specific database schema and desired data. - **Further Reading**: Consult the [n8n Docs on AI Agents](https://docs.n8n.io/advanced-ai/) for additional details and examples to expand your workflow's capabilities. - **Set Up a Website Chatbot**: Copy & Paste and replace the placeholders in the following code to embed the chatbot into your personal or company's website: [View in CodePen](https://codepen.io/olemai/pen/RNwPdVp) --- By following these steps, you will deploy a robust AI chatbot workflow that integrates with your MySQL database, allowing you to query data using natural language.
n8n$9.99Integrate OpenAI Responses API with n8n for Enhanced AI Workflows
This n8n workflow enables the integration of OpenAI's Responses API with existing AI workflows, allowing for seamless interaction with LLM and AI Agent nodes. It uses webhooks to intercept and remap requests for compatibility.
n8n$14.99Build a Multi-Model AI Chatbot with Telegram, AIMLAPI, and Google Sheets
This n8n workflow allows Telegram users to interact with multiple AI models dynamically. Users can select models using #model_id commands and track their daily usage via Google Sheets.
n8n$14.99Generate Text-to-Speech Using ElevenLabs via API
**Do you want to master AI automation, so you can save time and build cool stuff?** I've created a welcoming Skool community for non-technical yet resourceful learners. **[Join the AI Atelier](https://www.skool.com/the-ai-atelier-3311/about)** --- This workflow provides an API endpoint to generate speech from text using [Elevenlabs.io](http://go.n8n.ninja/elevenlabs), a popular text-to-speech service. ### Step 1: Configure Custom Credentials in n8n To set up your credentials in n8n, create a new custom authentication entry with the following JSON structure: ```json { "headers": { "xi-api-key": "your-elevenlabs-api-key" } } ``` Replace `your-elevenlabs-api-key` with your actual Elevenlabs API key. ### Step 2: Send a POST Request to the Webhook Send a POST request to the workflow's webhook endpoint with these two parameters: - `voice_id`: The ID of the voice from Elevenlabs that you want to use. - `text`: The text you want to convert to speech. This workflow has been a significant time-saver in my video production tasks. I hope it proves just as useful to you! Happy automating! The n8Ninja
n8n$4.99Chat with AI Models via OpenRouter Using Mistral
This n8n workflow demonstrates how to build an automated AI chat system using OpenRouter.ai. It includes a manual trigger, sets a model and user message, sends a POST request to the OpenRouter chat API, and summarizes the response. Workflow Steps: 1. Manual Trigger - Starts the workflow when executed manually. 2. Set Node - Defines: - Model: mistralai/mistral-small-3.2-24b-instruct:free - Message: What is the meaning of life? 3. HTTP Request - Sends a POST request to https://openrouter.ai/api/v1/chat/completions using Bearer Token Authentication with the model and message as JSON. 4. Summarize - Extracts and summarizes the AI's response (choices[0].message.content). Use Cases: - AI chatbot automation - Content summarization - Testing AI prompts in real-time - Educational demos using OpenRouter.ai - Lightweight conversational tools with no external server
n8n$4.99Automate Research Report Generation with Jina AI and Google Gemini
Transform a research question into a comprehensive, well-cited report using Jina AI for web crawling and Google Gemini for advanced summarization and report generation.
n8n$14.99Convert Text to Speech with Local KOKORO SDK
## Disclaimer The **Execute Command** node is only supported on **self-hosted** (local) instances of n8n. ## Introduction  **KOKORO S** - Kokoro S is a compact yet powerful text-to-speech model, currently available on Hugging Face and GitHub. Despite its modest size—trained on less than 100 hours of audio—it delivers impressive results, consistently topping the S leaderboard on Hugging Face. Unlike larger systems, Kokoro S offers the advantage of running locally, even on devices without GPUs, making it accessible for a wide range of users. **Who will benefit from this integration?** This will be useful for video bloggers, TikTokers, and it will also enable the creation of a free voice chat bot. Currently, S models are mostly paid, but this integration will allow for fully free voice generation. The possibilities are limited only by your imagination. #### Note Unfortunately, we can't interact with the KOKORO API via browser URL (GET/POST), **but** we can run a Python script through n8n and pass any variables to it. In the tutorial, the D drive is used, but you can rewrite this for any paths, including the C drive. ## Step 1 You need to have Python installed. [link](https://github.com/PierrunoY/Kokoro-S-Local) Also, download and extract the portable version of KOKORO from GitHub. Create a file named voicegen.py with the following code in the KOKORO folder: (C:\KOKORO). As you can see, the output path is: (D:\output.mp3). ``` import sys import shutil from gradio_client import Client # Set UTF-8 encoding for stdout sys.stdout.reconfigure(encoding='utf-8') # Get arguments from command line text = sys.argv[1] # First argument: input text voice = sys.argv[2] # Second argument: voice speed = float(sys.argv[3]) # Third argument: speed (converted to float) print(f"Received text: {text}") print(f"Voice: {voice}") print(f"Speed: {speed}") # Connect to local Gradio server client = Client("http://localhost:7860/") # Generate speech using the API result = client.predict( text=text, voice=voice, speed=speed, api_name="/generate_speech" ) # Define output path output_path = r"D:\output.mp3" # Move the generated file shutil.move(result[1], output_path) # Print output path print(output_path) ``` ## Step 2 Go to n8n and create the following workflow.  ## Step 3 Edit Field Module. ``` { voice: "af_sarah", text: "Hello world!" } ```  ## Step 4 We'll need an Execute Command module with the command: python ``` C:\KOKORO\voicegen.py "{{ $json.text }}" "{{ $json.voice }}" 1 ```  ## Step 5 The script is already working, but to listen to it, you can connect a Binary module with the path to the generated MP3 file ``` D:/output.mp3 ```  ## Step 6 Click “Next workflow” and enjoy the result. There are more voices and accents than in ChatGPT, plus it's free. ### P.S. If you want, there is a [detailed tutorial](https://blog.bswlife.site/2025/04/14/n8n-kokoro-tts-integration-setup/) on my blog.
n8n$4.99Real-Time Forex Sentiment Analysis & Alerts with Gemini AI to Discord
# Purpose & Audience Forex Market AI Analyst is an advanced n8n workflow template designed for Forex traders, analysts, prop firms, brokers, and trading communities who need real-time, actionable market intelligence. By combining multi-source news aggregation and AI-powered sentiment analysis, this workflow delivers both quick alerts and comprehensive sentiment reports for any currency pair directly to your Discord or chat platform. Stay ahead of market shifts and reduce manual research with automated, context-rich updates. ## What It Does 1. Aggregates breaking news and analysis from top Forex and macroeconomic sources for your selected currency pair. 2. Filters news by recency and relevance, ensuring only the most current and impactful headlines are included. 3. Analyzes market sentiment (bullish, bearish, or neutral) using a state-of-the-art language model (LLM). 4. Summarizes key themes, technical levels, and economic drivers in a clear, structured format with visual cues. 5. Delivers updates to your chosen Discord channel or chat group, with two distinct modes: - **Quick Alerts:** Fast, headline-focused updates for daily trading. - **Full Reports:** Detailed, multi-section sentiment breakdowns for weekly or in-depth review. Customizable date filters let you control how recent news must be for inclusion in sentiment analysis. ## Who Is It For? - Forex traders seeking an edge with instant, unbiased market sentiment. - Analysts and prop firms needing reliable, automated news curation and structured reporting. - Brokers and trading communities looking to enrich their channels with high-quality, automated market insights. - Anyone who wants a "set it and forget it" solution for monitoring any FX pair—no coding required. ## Setup Once, Use Forever - Deploy the workflow once and use it for a lifetime. - Duplicate for as many currency pairs as you need—customize the news sources or filters as you wish. - No recurring fees, no complex setup, and you control the update frequency and delivery channels. ## How to Set Up 1. Select your currency pair and adjust the news filter settings as desired. 2. Connect your AI model (Google Gemini or OpenAI) and Discord (or other chat) credentials. 3. Choose your alert mode: quick daily alerts, full weekly reports, or both. 4. Set your preferred schedule for updates. 5. Go live: Receive real-time, actionable FX news and sentiment in your Discord or chat, automatically. Forex Market AI Analyst—the all-in-one workflow for automated Forex news, sentiment, and technical updates. Perfect for traders, analysts, teams, and anyone who values timely, structured market intelligence.
n8n$14.99Automate Social Media Content Creation and Approval with WhatsApp and GPT-4
Streamline your social media content creation by sending a single WhatsApp message to generate AI-optimized posts for multiple platforms, complete with an approval workflow.
n8n$19.99Build Comprehensive Entity Profiles with GPT-4, Wikipedia & Vector DB for Content
This n8n template demonstrates how to build an intelligent entity research system that automatically discovers, researches, and creates comprehensive profiles for business entities, concepts, and terms. Use cases are many: try automating glossary creation for technical documentation, building standardized definition databases for compliance teams, researching industry terminology for content creation, or developing training materials with consistent entity explanations! ## Good to know Each entity research typically costs $0.08-$0.34, depending on the complexity and sources required. The workflow includes smart duplicate detection to minimize unnecessary API calls. The workflow requires multiple AI services and a vector database, so setup time may be longer than simpler templates. Entity definitions are stored locally in your Qdrant database and can be reused across multiple projects. ## How it works The workflow checks your existing knowledge base first to avoid duplicate research on entities you've already processed. If the entity is new, an AI research agent intelligently combines your vector database, Wikipedia, and live web research to gather comprehensive information. The system creates structured entity profiles with definitions, categories, examples, common misconceptions, and related entities - perfect for business documentation. AI-powered validation ensures all entity profiles are complete, accurate, and suitable for business use before storage. Each researched entity gets stored in your Qdrant vector database, creating a growing knowledge base that improves research efficiency over time. The workflow includes multiple stages of duplicate prevention to avoid unnecessary processing and API costs. ## How to use The manual trigger node is used as an example, but feel free to replace this with other triggers such as form submissions, content management systems, or automated content pipelines. You can research multiple related entities in sequence, and the system will automatically identify connections and relationships between them. Provide topic and audience context to get tailored explanations suitable for your specific business needs. ## Requirements - OpenAI API account for GPT-4-mini (entity research and validation) - Qdrant vector database instance (local or cloud) - Ollama with nomic-embed-text model for embeddings - **Automate Web Research with GPT-4, Claude & Apify for Content Analysis and Insights** workflow (for live web research capabilities) - Anthropic API account for Claude Sonnet 4 (used by the web research workflow) - Apify account for web scraping (used by the web research workflow) ## Customizing this workflow Entity research automation can be adapted for many specialized domains. Try focusing on specific industries like legal terminology (targeting official legal sources), medical concepts (emphasizing clinical accuracy), or financial terms (prioritizing regulatory definitions). You can also customize the validation criteria to match your organization's specific quality standards.
n8n$24.99Automate ArXiv Paper Trend Analysis and Newsletter Distribution
This workflow automates the process of gathering ArXiv papers based on user-defined categories and keywords, summarizes them using AI, and sends a newsletter to subscribers via Gmail.
n8n$19.99Create a Telegram Echo Bot for Debugging and Learning
This workflow sets up a Telegram echo bot that returns the JSON content of any message it receives, aiding in debugging and learning about Telegram's API.
n8n$3.99Automate LINE Chatbot Responses with Google Sheets and Google Gemini AI
This workflow automates AI-assisted replies for LINE Official Account messages, using Google Sheets to store and reference chat history, ensuring contextual and personalized interactions.
n8n$14.99Create an On-Premises AI Assistant for Kaggle Competitions Using Qdrant and Ollama
Develop a domain-specific AI assistant for Kaggle competitions using n8n, Qdrant, and Ollama. This workflow supports real-time Python coding assistance, document ingestion, and retrieval-augmented generation, all hosted on-premises for enhanced privacy.
n8n$14.99Automate Blog Creation with AI and Google Sheets Integration
This n8n workflow automates the end-to-end process of generating, evaluating, and publishing SEO-friendly blog content using AI and Google Sheets. Ideal for marketing teams and content creators aiming to streamline their content pipeline.
n8n$9.99Develop AI Agents with Custom Reasoning Using GraphRAG and Ontologies
This workflow enables the creation of AI agents in n8n that utilize custom reasoning patterns defined by a knowledge ontology. It leverages InfraNodus and GraphRAG to provide AI agents with a unique way of thinking, applicable to various problem-solving scenarios.
n8n$4.99Create a Personal Portfolio Chatbot with Automated Email Summaries
Develop a professional personal portfolio chatbot that integrates RAG functionality, stores conversations, and sends daily email summaries.
n8n$19.99Voice Creation, SFX, Sound Effects, Voice Changer & More! Elevenlabs MCP Server
Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator? [Join the community](https://www.skool.com/beyond-nodes-automation-lab-2006/about) This workflow provides a complete set of tools for interacting with the ElevenLabs voice API, enabling AI-powered text-to-speech, voice management, and audio processing capabilities. ## Features ### Text-to-Speech Operations - Convert text to speech with customizable voice settings - Generate speech with timestamps for precise audio control - Stream text-to-speech in real-time - Stream text-to-speech with timestamps for live applications ### Voice Management - List all available voices - Get detailed information about specific voices - Delete custom voices - Edit voice properties (name and description) - Find similar voices based on voice ID ### Audio Processing - Create transcripts from audio - Apply voice changing effects - Generate sound effects - Isolate audio components - Design and preview new voices - Save voice previews as new voices ## Requirements - An ElevenLabs API key - n8n instance with HTTP Request tool node - MCP Server Trigger node for AI integration ## Setup 1. Import the workflow into your n8n instance 2. Configure your ElevenLabs API key in the workflow settings 3. The workflow uses AI expressions for voice IDs with a fallback value of `Z9hrfEHGU3dykHntWvIY` ## Usage All nodes are connected to the MCP Server Trigger for AI-powered interactions ### Example Use Cases - Generate natural-sounding speech from text - Create and manage custom voices - Process and transform audio files - Build voice-based applications - Integrate ElevenLabs capabilities into existing workflows ## Technical Details - All endpoints use proper error handling - Voice ID parameters use AI expressions with fallback values - Nodes are organized in logical groups for better workflow management - Includes comprehensive parameter validation - Supports streaming and real-time processing ## Support For issues or questions, please refer to: - [ElevenLabs API Documentation](https://docs.elevenlabs.io) - [n8n Documentation](https://docs.n8n.io) - [n8n Community](https://community.n8n.io)
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