This article provides a complete, practical walkthrough of the Http Executeworkflow Send Webhook n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:  
   Build a Conversational AI Agent in n8n to Recommend Activities Using the Bored API
   
   Meta Description:  
   Discover how to build an interactive AI agent in n8n that chats with users and suggests personalized activity ideas by integrating OpenAI and the Bored API. Ideal for automation enthusiasts exploring conversational workflows.
   
   Keywords:  
   n8n workflow, OpenAI GPT-4o, Bored API, conversational AI, AI agent, automation, no-code workflow, LangChain, chatbot suggestion tool, activity suggestion, n8n AI, HTTP Request Node
   
   Third-Party APIs Used:
   
   - OpenAI API (via GPT-4o-mini for chat and AI inference)
   - Bored API (https://bored-api.appbrewery.com/filter)
   
   ---
   
   Article:  
   
   # Building a Conversational AI Bot in n8n to Suggest Activities Using OpenAI and the Bored API
   
   If you've ever felt stuck wondering what to do next, this creative automation project might be the answer. With just a few clever nodes, n8n's powerful automation platform lets you build an AI-powered chatbot that recommends fun, purposeful, or relaxing activities—drawing suggestions from the quirky but useful Bored API and powered by the intelligence of OpenAI's GPT-4o model.
   
   In this article, we’ll break down an example n8n workflow that combines conversational AI with a sub-workflow calling an external activity suggestion API. The result? A chatbot that listens, understands, and responds with something engaging for users to try.
   
   ## Overview: What This Workflow Does
   
   This n8n setup includes two main parts:
   
   - A primary AI agent that engages with user chats.
   - A sub-workflow (used as a tool) that analyzes user intent and queries the Bored API for a suitable suggestion.
   
   Let’s walk through the components and how they work together to deliver a dynamic conversational experience.
   
   ---
   
   ## Components in Detail
   
   ### 1. Trigger: Starting the Conversation
   
   The interaction begins with the “When chat message received” node. This trigger listens for incoming chat messages, such as:
   
   > “Hi! Please suggest something to do. I feel like learning something new.”
   
   This input flows into an AI agent node that powers the conversation logic.
   
   ---
   
   ### 2. The AI Agent
   
   At the heart of the experience is the “AI Agent” node, connected to three critical components:
   
   - **OpenAI Chat Model**: GPT-4o-mini acts as the large language model handling the core understanding of user intent.
   - **Simple Memory**: A memory buffer to recall past interactions during the conversation.
   - **Custom Tool: Activity Tool**: A LangChain tool that allows the agent to call a sub-workflow (“activity_tool”) if it detects the user is seeking something to do.
   
   With these integrated, the AI agent behaves like a thoughtful assistant that doesn’t just chat but takes meaningful action.
   
   ---
   
   ### 3. Sub-Workflow: Calling the Bored API
   
   When a user expresses boredom or a desire for suggestions, the “Activity Tool” subprocess activates.
   
   This sub-workflow contains several smart steps:
   
   - **Trigger: When Executed by Another Workflow** – Accepts the chat input passed from the AI Agent.
   - **Information Extraction** – Uses another GPT-4o call to extract structured intents like activity "type" (educational, recreational, charity, etc.) and number of participants.
   - **HTTP Request: Call the Bored API** – Based on the extracted info, this HTTP request sends a query to https://bored-api.appbrewery.com/filter.
     - Example params: type=education, participants=1
   - **Aggregate and Format the Activity Suggestion** – Combines and prettifies the result.
   - **Set Response** – Finalizes the suggestion into a returnable variable the AI agent can present in natural language.
   
   The beauty of this modularity is that the tool can be reused and updated independently, working seamlessly inside the conversational flow.
   
   ---
   
   ### 4. The Result: Chatbot with Utility
   
   Once powered, users can interact with the AI Agent like this:
   
   > User: “I’m bored. Any idea what I could try on my own?”
   
   > AI Agent: “How about learning how to draw in pencil? It’s fun and relaxing. Want resources to get started?”
   
   The AI agent smartly picks up the request, extracts semantic meaning, and queries the right external resource to provide an engaging response—all done with zero code, thanks to n8n.
   
   ---
   
   ## Try It Yourself
   
   From within your n8n instance:
   
   🗨️ Click the **Chat** area and type:
   > Hi! Please suggest something to do. I feel like learning something new.
   
   Then watch the workflow kick into action, pulling an activity from the Bored API based on your intent.
   
   ---
   
   ## Next Steps
   
   This foundational workflow can be extended even further:
   
   - Integrate calendar or location APIs to suggest local events or schedule breaks.
   - Add multiple tools for other forms of recommendations—like recipes, books, or coding challenges.
   - Connect to a messaging platform like Slack, Discord, or Telegram to make it publicly usable.
   
   Want to take it to the next level? Explore [Advanced AI techniques in n8n](https://docs.n8n.io/advanced-ai/) and learn how to integrate vector stores, custom prompts, or external agents.
   
   ---
   
   ## Conclusion
   
   This workflow is more than just a chatbot—it’s a prime example of how n8n can combine no-code logic, AI, and public APIs to create real-time, intelligent automation. Whether you're building for personal use or embedding helpful assistants in your app or website, this modular and powerful design bridges the gap between AI and action.
   
   Happy automating!

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.