Create an eBay Item Feed Service API Gateway for AI Agents

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Built by David Ashby David Ashby
Created on June 07, 2026

Description

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Complete MCP server exposing 4 Item Feed Service API operations to AI agents.

⚡ Quick Setup

Import this workflow into your n8n instance
Credentials Add Item Feed Service credentials
Activate the workflow to start your MCP server
Copy the webhook URL from the MCP trigger node
Connect AI agents using the MCP URL

🔧 How it Works

This workflow converts the Item Feed Service API into an MCP-compatible interface for AI agents.

• MCP Trigger: Serves as your server endpoint for AI agent requests
• HTTP Request Nodes: Handle API calls to https://api.ebay.com/buy/feed/v1_beta
• AI Expressions: Automatically populate parameters via $fromAI() placeholders
• Native Integration: Returns responses directly to the AI agent

📋 Available Operations (4 total)

🔧 Item (1 endpoints)

• GET /item: Download Hourly Snapshot Feed

🔧 Item_Group (1 endpoints)

• GET /item_group: Get Item Group

🔧 Item_Priority (1 endpoints)

• GET /item_priority: Get Item Priority

🔧 Item_Snapshot (1 endpoints)

• GET /item_snapshot: Get Item Snapshot

🤖 AI Integration

Parameter Handling: AI agents automatically provide values for:
• Path parameters and identifiers
• Query parameters and filters
• Request body data
• Headers and authentication

Response Format: Native Item Feed Service API responses with full data structure

Error Handling: Built-in n8n HTTP request error management

💡 Usage Examples

Connect this MCP server to any AI agent or workflow:

• Claude Desktop: Add MCP server URL to configuration
• Cursor: Add MCP server SSE URL to configuration
• Custom AI Apps: Use MCP URL as tool endpoint
• API Integration: Direct HTTP calls to MCP endpoints

✨ Benefits

• Zero Setup: No parameter mapping or configuration needed
• AI-Ready: Built-in $fromAI() expressions for all parameters
• Production Ready: Native n8n HTTP request handling and logging
• Extensible: Easily modify or add custom logic

> 🆓 Free for community use! Ready to deploy in under 2 minutes.