MCP server on n8n for AI agents to access NPR API for a

This automation template enables AI agents to interact with the NPR Listening Service API via a standardized HTTP interface built on n8n and the MCP protocol. The workflow exposes 9 core operations — from personalized recommendations to rating submissions — allowing seamless integration of NPR audio content into AI-driven applications. Ideal for developers building voice assistants or AI-first platforms requiring rich audio data.

## Who it´s for
- AI agent developers integrating NPR audio content
- Product teams adding personalized podcasts to their apps
- Automation specialists expanding MCP compatibility of their systems

## What the automation does
- Exposes NPR Listening Service API as an MCP-compatible interface for AI agents
- Handles 9 types of operations via HTTP triggers: recommendations, search, channels, ratings, etc.
- Dynamically populates request parameters using $fromAI() expressions from the AI agent
- Returns responses directly in the original API format without transformation
- Uses OAuth2 for secure user authentication

## What´s included
- Ready-to-run n8n workflow with MCP support
- Logic for processing HTTP requests from AI agents
- Integrations with NPR Listening Service API and external AI agents
- Basic text instructions for deployment and adaptation

## Requirements for setup
- n8n instance (self-hosted or cloud)
- Access to NPR Listening Service API with valid OAuth2 credentials
- Compatible AI agent capable of making HTTP calls

## Benefits and outcomes
- Accelerates integration of AI agents with NPR’s audio platform
- Preserves original API structure and semantics
- Lowers entry barrier for MCP-compliant solutions
- Simplifies scalability through pre-built operations
- Enables flexibility via dynamic parameter handling

## Important: template only
Important: you are purchasing a ready-made automation workflow template only. Rollout into your infrastructure, connecting specific accounts and services, 1:1 setup help, custom adjustments for non-standard stacks and any consulting support are provided as a separate paid service at an individual rate. To discuss custom work or 1:1 help, contact via Telegram: @gleb923.