This n8n workflow creates an MCP (Meta Cloud Platform) server interface for eBay’s Analytics API, enabling AI agents to monitor and manage API call limits effectively. It automates the process of fetching application and user rate limits, providing real-time insights into API usage to prevent overages.

The workflow begins with a MCP trigger node that listens for requests from AI agents on a designated endpoint. Two main HTTP request nodes are configured to call eBay’s ‘getRateLimits’ and ‘getUserRateLimits’ endpoints, respectively. These nodes are set up with OAuth2 authentication, which is securely managed within n8n. Parameters for API calls are dynamically populated using `$fromAI()` expressions to tailor requests based on the needs of the AI agent.

The first HTTP request retrieves application-wide call limits, showing remaining quota, reset times, and usage statistics. The second HTTP request provides user-specific rate limits with similar data points. Sticky notes are included within the workflow as visual aids to distinguish between application-level and user-level limits.

This setup is particularly useful for developers and system administrators managing high-volume API interactions on eBay, ensuring they stay within usage quotas while allowing AI-driven automation and monitoring. By transforming raw API data into a structured MCP interface, the workflow supports proactive management of API calls, preventing service disruptions and optimizing API usage.