This n8n workflow creates an MCP-compatible interface for the NPR Listening Service API, enabling seamless integration of NPR audio content and personalized recommendations with AI agents. It handles multiple endpoints including recommendations, channels, history, organizations, promos, ratings, and search. The workflow starts with an MCP trigger that listens for incoming requests from AI agents, and then processes these requests via HTTP Request nodes to NPR’s API endpoints. It utilizes dynamic parameter population with $fromAI() expressions for customization and flexibility. The responses are structured to match the API’s original format, making it suitable for use in intelligent applications or chatbots that deliver tailored audio content or user-specific media suggestions. This workflow is particularly useful for developers building AI-powered news or podcast apps that require an automated, scalable way to fetch and interact with NPR content.
NPR Listening Service MCP Integration Workflow
| Node Count | 11 – 20 Nodes |
|---|---|
| Nodes Used | @n8n/n8n-nodes-langchain.mcpTrigger, httpRequestTool, stickyNote |
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