Complete MCP server exposing 9 NPR Listening Service API operations to AI agents.
This workflow converts the NPR Listening Service API into an MCP-compatible interface for AI agents.
• MCP Trigger: Serves as your server endpoint for AI agent requests
• HTTP Request Nodes: Handle API calls to https://listening.api.npr.org
• AI Expressions: Automatically populate parameters via $fromAI()
placeholders
• Native Integration: Returns responses directly to the AI agent
• GET /v2/aggregation/{aggId}/recommendations: Get a set of recommendations for an aggregation independent of the user's lis...
• GET /v2/channels: List Available Channels
• GET /v2/history: Get User Ratings History
• GET /v2/organizations/{orgId}/categories/{category}/recommendations: Get a list of recommendations from a category of content from an organization
• GET /v2/organizations/{orgId}/recommendations: Get a variety of details about an organization including various lists of rec...
• GET /v2/promo/recommendations: Get Recent Promo Audio
• POST /v2/ratings: Submit Media Ratings
• GET /v2/recommendations: Get User Recommendations
• GET /v2/search/recommendations: Get Search Recommendations
Parameter Handling: AI agents automatically provide values for:
• Path parameters and identifiers
• Query parameters and filters
• Request body data
• Headers and authentication
Response Format: Native NPR Listening Service API responses with full data structure
Error Handling: Built-in n8n HTTP request error management
Connect this MCP server to any AI agent or workflow:
• Claude Desktop: Add MCP server URL to configuration
• Cursor: Add MCP server SSE URL to configuration
• Custom AI Apps: Use MCP URL as tool endpoint
• API Integration: Direct HTTP calls to MCP endpoints
• Zero Setup: No parameter mapping or configuration needed
• AI-Ready: Built-in $fromAI()
expressions for all parameters
• Production Ready: Native n8n HTTP request handling and logging
• Extensible: Easily modify or add custom logic
🆓 Free for community use! Ready to deploy in under 2 minutes.