This article provides a complete, practical walkthrough of the Respondtowebhook Stickynote Automation 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:
   Automate Instagram Conversations with AI Using n8n and ManyChat: A No-Code Guide
   
   Meta Description:
   Discover how to build an intelligent Instagram chatbot using n8n, ManyChat, and ChatGPT. Learn how to automate DMs, deliver influencer-style responses, and maintain contextual memory with a no-code setup.
   
   Keywords:
   Instagram automation, n8n workflow, ManyChat integration, ChatGPT chatbot, AI influencer bot, Instagram DMs, no-code chatbot, AI assistant for Instagram, LangChain AI agent, memory buffer AI
   
   Article:
   
   Automating Instagram DMs with AI: A No-Code Solution Using n8n, ManyChat, and ChatGPT
   
   As Instagram continues to dominate the social media landscape, creators and businesses are constantly exploring new ways to engage with their audiences efficiently. Responding to messages in a timely and personalized manner can be overwhelming, particularly for influencers and brand pages with large followings. Enter the world of no-code automation.
   
   In this article, we’ll explore a powerful yet accessible n8n workflow named “InstaTest,” which leverages ManyChat, n8n.io, and OpenAI's ChatGPT to automate Instagram DM responses. Designed specifically for influencer-style conversations, this solution combines custom AI prompts, contextual memory, and seamless webhook communication to simulate human-like responses — all without writing a single line of code.
   
   Overview: What Does the Workflow Do?
   
   The "InstaTest" workflow is a ready-to-deploy automation designed to:
   1. Receive incoming Instagram messages via ManyChat.
   2. Set a personalized AI system prompt tailored to an influencer’s writing style.
   3. Use ChatGPT and LangChain to generate contextual replies.
   4. Send the reply back to the subscriber on Instagram via ManyChat.
   
   Let’s break down each component.
   
   🧩 Workflow Components and Logic
   
   1. Receiving Messages via ManyChat Webhook
   This setup starts with a webhook node in n8n, named "Getting message from Instagram." It listens for POST requests from ManyChat, a chatbot builder that connects Instagram with external services. This webhook acts as the entry point, receiving user messages and session metadata.
   
   2. System Prompt Configuration
   In "Set your system promt for AI" (note the spelling in the node name), the workflow defines parameters the AI needs to generate relevant responses. These include:
   - The user's message (chatInput),
   - A unique session ID for managing chat history,
   - The system prompt that instructs the AI to respond as a social media influencer, with a particular writing style.
   
   Example prompt used:
   Persona: You are an Instagram influencer.
   Context: You receive messages from your subscribers.
   Task: Answer questions in your writing style and patterns according to your previous posts. Use your post only as style and tone reference.
   Style Rules: simple answers
   
   3. AI Processing via ChatGPT and LangChain
   Two important modules — a ChatGPT model and a LangChain AI Agent — come into play here:
   - The ChatGPT node connects to OpenAI (via API credentials) and serves as the engine behind the natural-language response generation.
   - The LangChain “AI Agent” takes the prompt and user input from the previous steps to craft a response.
   
   4. Preserving Chat Context Across Sessions
   To provide intelligent, contextual answers, the workflow uses the LangChain-based “Local n8n memory” node. This stores up to 20 recent messages for each user session, enabling more natural back-and-forth conversations with continuity.
   
   5. Returning the Response to Instagram
   Finally, the “Send respond” node sends the AI-crafted reply back to ManyChat, which delivers the response to the user on Instagram.
   
   All of this happens automatically and in real time with zero manual intervention.
   
   🎛️ Customization Highlights
   
   The workflow includes sticky notes acting as documentation directly within n8n. These notes guide users on what can be edited:
   - The webhook URL can be copied into ManyChat’s custom action for real-time message capture.
   - You can modify the AI's behavior by editing the initial system prompt.
   - In the AI block, you can choose your preferred ChatGPT model (e.g. GPT-3.5 or GPT-4).
   - Update how much chat history is kept by adjusting the context window in the memory block.
   
   🔗 Third-Party APIs and Tools Used
   
   1. ManyChat
   🌐 https://manychat.com  
   Purpose: Sends and receives Instagram messages via webhook integration.
   
   2. OpenAI API (ChatGPT)
   🌐 https://platform.openai.com  
   Purpose: Processes text input and generates conversational replies based on system instructions.
   
   3. LangChain (via n8n LangChain nodes)
   🌐 https://www.langchain.com  
   Purpose: Provides advanced memory and logic handling for AI-driven applications, operational through n8n’s integrated nodes.
   
   🚀 Why Use This Automation?
   
   - Saves time and energy for influencers handling large volumes of messages.
   - Ensures brand consistency by enforcing a defined tone and style.
   - Maintains conversational history for continuity, leading to more natural communication.
   - Fully no-code and beginner-friendly with detailed instructions included.
   
   📘 Helpful Resources
   
   - Guide in Notion for setup: Instagram GPT (light version): https://shadowed-pound-d6e.notion.site/Instagram-GPT-light-version-Manychat-X-N8N-176293bddff880899a9ac255585d29f7?pvs=4
   - ManyChat link: https://manychat.partnerlinks.io/vm4wkw8j81tc
   
   Conclusion
   
   The “InstaTest” n8n workflow is a powerful example of how no-code tools can streamline everyday digital processes. Whether you're an influencer, a brand ambassador, or a social media manager, this automation enables you to maintain engagement with your audience while saving valuable time. With integrations like OpenAI and ManyChat, even non-developers can harness the power of conversational AI.
   
   Ready to humanize your Instagram DMs with automation? All it takes is a few drag-and-drop nodes in n8n.
   
   — Written by Your AI Assistant 🤖

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.