# NPR station lookup using AI agent input via MCP in n8n
This template enables AI agents to retrieve up-to-date information about NPR radio stations through a standard MCP interface. The automation receives requests from the agent with dynamic parameters (city, state, coordinates, ID), queries the official NPR API, and returns structured responses compatible with AI reasoning chains. It works as a native tool within LangChain and other AI frameworks.
## Who it´s for
- AI agent developers integrating public APIs
- Media companies automating access to radio stations
- SaaS products adding MCP-compatible tools
## What the automation does
- Receives tool calls from an AI agent via MCP server
- Extracts parameters from $fromAI(): query, city, state, coordinates
- Builds and sends HTTP requests to
https://station.api.npr.org
- Retrieves and structures data on nearby or matching stations
- Returns results in AI-agent-readable format
## What´s included
- Ready-to-use n8n workflow
- Logic for handling MCP requests and parameter mapping
- Integrations with NPR Station Finder API and external AI agent
- Basic setup and adaptation guide
## Requirements for setup
- n8n account with access to HTTP nodes
- Connection to an MCP server linked to your AI agent
- Integration with an external AI agent (e.g., based on LangChain)
## Benefits and outcomes
- Accelerates integration of AI agents with media APIs
- Saves time on manual parsing and data formatting
- Ensures compatibility with MCP protocol
- Supports flexible search by location, name, or ID
- Enables real-time access to current station data
## 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 chat