Complete eBay Feed API Integration for AI Agents with MCP Server

Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

Join the community

Complete MCP server exposing 23 Feed API operations to AI agents.

⚑ Quick Setup

  1. Import this workflow into your n8n instance
  2. Credentials Add Feed API credentials
  3. Activate the workflow to start your MCP server
  4. Copy the webhook URL from the MCP trigger node
  5. Connect AI agents using the MCP URL

πŸ”§ How it Works

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

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

πŸ“‹ Available Operations (23 total)

πŸ”§ Customer_Service_Metric_Task (3 endpoints)

β€’ GET /customer_service_metric_task: Get Customer Service Metric Task
β€’ POST /customer_service_metric_task: Create/Search Customer Service Metric Task
β€’ GET /customer_service_metric_task/{task_id}: Get {Task Id}

πŸ”§ Inventory_Task (3 endpoints)

β€’ GET /inventory_task: Get Inventory Task
β€’ POST /inventory_task: Create/Search Inventory Task
β€’ GET /inventory_task/{task_id}: Get {Task Id}

πŸ”§ Order_Task (3 endpoints)

β€’ GET /order_task: Get Order Task
β€’ POST /order_task: Create/Search Order Task
β€’ GET /order_task/{task_id}: This method retrieves the task details and status of the specified task

πŸ”§ Schedule (6 endpoints)

β€’ GET /schedule: Get Schedule Template
β€’ POST /schedule: Create/Search Schedule
β€’ DELETE /schedule/{schedule_id}: This method deletes an existing schedule
β€’ GET /schedule/{schedule_id}: This method retrieves schedule details and status of the specified schedule
β€’ PUT /schedule/{schedule_id}: This method updates an existing schedule
β€’ GET /schedule/{schedule_id}/download_result_file: This method downloads the latest result file generated by the schedule

πŸ”§ Schedule_Template (2 endpoints)

β€’ GET /schedule_template: Get Schedule Template
β€’ GET /schedule_template/{schedule_template_id}: This method retrieves the details of the specified template

πŸ”§ Task (6 endpoints)

β€’ GET /task: Upload Task File
β€’ POST /task: This method creates an upload task or a download task without filter criteria
β€’ GET /task/{task_id}: This method retrieves the details and status of the specified task
β€’ GET /task/{task_id}/download_input_file: Get Download Input File
β€’ GET /task/{task_id}/download_result_file: Get Download Result File
β€’ POST /task/{task_id}/upload_file: Create/Search Upload File

πŸ€– AI Integration

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

Response Format: Native Feed API responses with full data structure

Error Handling: Built-in n8n HTTP request error management

πŸ’‘ Usage Examples

Connect this MCP server to any AI agent or workflow:

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

✨ Benefits

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

πŸ†“ Free for community use! Ready to deploy in under 2 minutes.