More and more businesses are adopting AI-driven chat experiences to streamline support, qualify leads, and provide real-time assistance. What if you could build your own conversational agent without deep coding experience or expensive SaaS tools? With the open-source automation platform n8n, you can. In this guide, we’ll show you exactly how to build a powerful and flexible n8n conversational agent that integrates easily with tools like OpenAI, Slack, Telegram, and more.
Whether you're a startup founder, solopreneur, or automation enthusiast, this low-code approach can help you deploy your own chatbot customized to your workflows — all while keeping control over your data.
What Is a Conversational Agent in n8n?
A conversational agent is an automated system that interacts with users via natural language — usually through chat platforms. In n8n, this means building a workflow that receives a user message, generates a response using a model (like OpenAI), and sends it back to the user.
This is possible thanks to n8n’s node-based system, which integrates with LLMs (like GPT) and messaging services using a drag-and-drop interface. No backend coding required.
Tools You'll Need
Before you start, you’ll want to have these set up:
- n8n installed (self-hosted or cloud)
- Access to OpenAI API (or any LLM with an API)
- Messaging platform setup, e.g., Telegram, Slack, Discord
- An idea or use case for your chatbot (support, recommendations, assistant)
If you haven't installed n8n yet, check out our step-by-step Docker guide or choose the easiest Windows setup if you're just testing locally.
Step-by-Step: Build a Basic n8n Conversational Agent
Let’s walk through a simple example: a Telegram-based chatbot that responds to user queries using OpenAI’s GPT model.
Step 1: Get Your Telegram Bot Token
- Open Telegram and search for @BotFather.
- Use the
/newbotcommand and follow the prompts. - Copy the Telegram Bot Token, you'll need this in n8n.
Step 2: Create Your n8n Workflow
- Log into your n8n instance or start here with their cloud platform.
- Create a new workflow and add the Telegram Trigger node.
- Paste your bot token.
- Choose "message" as the update type.
- Add an OpenAI Node next.
- Choose the model (e.g.,
gpt-3.5-turbo). - Set System Prompt to something like:
“You are a helpful assistant for tech support questions.” - Map the incoming user message to the prompt.
- Choose the model (e.g.,
Here’s a simple visual layout of your node sequence:
| Node | Description |
|---|---|
| Telegram Trigger | Captures incoming messages |
| OpenAI or LLM Node | Processes the user question |
| Telegram Node | Sends the LLM response back to the user |
Step 3: Return the Response
- Add a Telegram Send Message node.
- Use the same token.
- Send the response generated from OpenAI back to the user.
- Make sure to map the correct Chat ID to ensure reply goes to the user.
Step 4: Save and Enable
- Name your workflow something like "Telegram Chatbot".
- Click Activate Workflow.
Within seconds, your Telegram bot will be live and able to handle conversations!
Example Use Cases for Conversational Agents in n8n
You can go beyond basic Q&A. Here are some practical ways to enhance your n8n conversational agent:
-
Customer Support Assistant
Pull in order info from Shopify, CRM tools, or databases using n8n’s built-in integrations. -
Meeting Scheduler
Connect to Google Calendar and suggest meeting times in the conversation flow. -
AI Travel Agent
Use external APIs to fetch flights, hotel info, and generate responses using GPT. -
Internal Slack Copilot
Trigger internal knowledge base lookups (Notion, Airtable, etc.) and serve users directly in Slack.
If you're working with AI tools like CrewAI, Flowise, or LangChain, you might also enjoy reading Flowise vs n8n for a broader overview of LLM agent options.
Tips to Enhance Your n8n Chatbot
Here are a few pro-level suggestions as you scale your automation:
- Store User Sessions: Use IF nodes or n8n Variables to preserve user context or memory.
- Rate Limiting & Throttling: Avoid API overuse by adding Wait timers or webhook conditions.
- Custom Components: Want more control? Check out how to install community packages and extend with custom nodes.
You can also monitor system stability using error handling best practices, especially when dealing with unpredictable APIs like LLMs.
Use Case Expansion: Multi-Channel Agents
Once your conversational agent is working on one channel (like Telegram), you can replicate the same for other platforms:
- Slack: Use Slack Trigger and Send Message nodes.
- Messenger/WhatsApp: Integrate via third-party services or APIs.
- Web: Build a chatbot UI with your front-end and connect using Webhook triggers.
With n8n’s flexibility, you can orchestrate complex multi-modal agents using the same drag-and-drop logic.
Using Your n8n Conversational Agent with Other Apps
n8n supports hundreds of native integrations. Here’s just a small sample of what you can tie into your chatbot flows:
- Airtable or Notion for data lookups
- MySQL or PostgreSQL for structured data
- Twilio for SMS-based conversations
- CRMs like Hubspot or Zoho for lead capture
- Google Sheets for logging conversations
With automation tools like Make.com or Zapier often lacking affordable LLM support, n8n provides tremendous value, especially for power users focused on open-source customization.
Final Thoughts
Building a conversational agent with n8n isn’t just about chatbots — it’s about combining automations with AI to create a responsive layer between your users and your backend systems. With access to open-source flexibility and no vendor lock-in, n8n empowers you to move beyond boring bots to design AI experiences that feel tailored, helpful, and scalable.
Ready to build your AI agent? Start building with n8n and own your automations without the SaaS bloat.
FAQ
How much does it cost to run a conversational agent with n8n?
If you're self-hosting n8n, it's free (just pay for your server). The only cost is typically the API usage for services like OpenAI. If you're using n8n Cloud, there's a free trial and then affordable pricing tiers.
Can I use LLMs other than OpenAI?
Yes! n8n supports HTTP Request nodes, so you can integrate any LLM with an API—like Anthropic’s Claude, Hugging Face models, local Ollama, or even Azure OpenAI.
How do I keep user context without a database?
You can use n8n’s built-in memory using Variables or save temporary state in Workflow Data, but for persistent conversations, consider integrating Airtable, Redis, or a database node.
Is this better than using Make.com or Zapier for chatbots?
For simple workflows, Make or Zapier might be fine. But if you want powerful branching logic, retry handling, or full control over hosting and LLM integration, n8n gives you far more flexibility.
Can I deploy this on my own machine?
Absolutely! n8n runs great locally or on servers — Windows, macOS, Linux, even a Raspberry Pi. Use our self-hosted setup to get started in under 30 minutes.