This n8n workflow creates an interface for accessing NPR station data via an MCP (MetaCommunication Protocol) server, making it easy for AI agents to retrieve NPR station information. The main goal is to convert the NPR Station Finder API into a reliable MCP-compatible service that responds to client requests.

The workflow begins with the ‘NPR Station Finder Service MCP Trigger,’ a webhook that listens for incoming requests from AI agents or clients. When triggered, it activates the workflow, which then can perform multiple operations.

Two primary nodes handle the API interaction:

– ‘Get Stations 1’: An HTTP Request node that queries the NPR API to list stations based on search parameters such as station name, city, state, latitude, and longitude. These parameters are dynamically populated using AI expressions, allowing customizable and flexible requests.

– ‘Get Station 1’: When a specific station ID is provided, this node fetches detailed metadata for that station from the NPR API.

Throughout, the workflow employs authorization credentials to securely access the NPR API and API response data is directly returned to the requesting AI agent or client, facilitating seamless integration.

Practical use cases include dynamically searching for NPR stations based on user-input criteria or fetching detailed station data for embedding in apps, websites, or chatbots. This setup is ideal for media organizations, developers building radio-related apps, or any service requiring real-time NPR station data accessible via a standardized API interface.