Complete MCP server exposing 9 NPR Listening Service API operations to AI agents.
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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.