AI Stock & Price Chatbot for n8n with HTTP Catalog Tools

Answer product price & availability in real time—without dumping your whole catalog into the AI

This n8n workflow adds an OpenAI-powered AI Stock & Price Chatbot that searches your store catalog via Feedpipe, retrieves live pricing/stock, and returns product links—using only the latest successfully updated data.

What this workflow does

• Connects your store feed to Feedpipe so product data is imported and kept current through Feedpipe’s automatic updates.
• Accepts customer questions through an n8n Chat interface.
• The AI agent interprets the request and uses function calling to call two catalog tools:
  • search_shop_catalog: searches by the customer’s query with optional price and availability filters.
  • get_shop_product: retrieves a specific product when the user provides an exact `SKU`.
• Builds responses using returned prices, stock information, and product links.
• Follows agent instructions to avoid confirming unknown availability, and requests price confirmation when catalog data is marked as stale.
• Uses search results (not the full catalog) to help reduce token usage and minimize invented product details.

Use cases

• Customer asks: “Do you have this in stock?” → chatbot checks availability and replies with a product link.
• Query like: “Show me running shoes under $50” → search tool applies price filters and returns matching items.
• Support agent provides an exact SKU → chatbot returns the correct product details and current price.
• SaaS operator needs a lightweight AI product inquiry layer without exposing the full catalog to the model.

Technical details

• Feedpipe API integration (requires Feedpipe API URL, shop identifier, and shop API key; catalog import + first successful update first).
• n8n nodes/tools used: n8n-nodes-langchainchat trigger, n8n-nodes-langchainlm (OpenAI Chat Model), n8n-nodes-langchainagent, HTTP Request tool for catalog calls, and n8n-nodes-langchainmemory (memory buffer window) for chat context.
• Agent uses search_shop_catalog and get_shop_product functions to fetch only relevant product data.