# MCP server on n8n: AI agents fetch bicycle incident data from BikeWise API
This automation template enables AI agents to directly query structured bicycle incident data via a standardized MCP interface. It translates AI tool calls into HTTP requests to BikeWise API v2 and returns responses seamlessly—ideal for integrating open urban data into AI workflows.
## Who it´s for
- AI developers integrating public APIs as tools in agent systems.
- Urban data analysts focusing on cycling safety and infrastructure.
- City planners using geospatial data for transportation risk assessment.
## What the automation does
- Receives AI agent requests via MCP trigger.
- Maps $fromAI() parameters to BikeWise API-compatible format.
- Sends GET requests to four endpoints: paginated incidents, single incident lookup, locations, and markers.
- Returns structured responses, including GeoJSON, directly to the AI agent.
- Enables seamless integration without custom coding.
## What´s included
- Ready-to-use n8n workflow.
- Logic for handling MCP requests and parameter mapping.
- Integrations with BikeWise API v2 and MCP Server.
- Basic text guide for setup and adaptation.
## Requirements for setup
- n8n instance with access to MCP Server.
- Access to BikeWise API v2 (public or with required key).
- AI agent framework supporting MCP tools (e.g., LangChain-based).
## Benefits and outcomes
- Accelerates integration of open urban data into AI agents.
- Eliminates manual parsing or intermediate data processing.
- Enables real-time access to geospatial incident data for analysis.
- Lowers technical barrier for non-developers using AI with external APIs.
## 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
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