Complete Lyft API integration for AI agents with 16 operations using MCP
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Complete MCP server exposing 16 Lyft API operations to AI agents.
⚡ Quick Setup
- Import this workflow into your n8n instance
- Credentials Add Lyft credentials
- Activate the workflow to start your MCP server
- Copy the webhook URL from the MCP trigger node
- Connect AI agents using the MCP URL
🔧 How it Works
This workflow converts the Lyft 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://api.lyft.com/v1
• AI Expressions: Automatically populate parameters via $fromAI() placeholders
• Native Integration: Returns responses directly to the AI agent
📋 Available Operations (16 total)
🔧 Cost (1 endpoints)
• GET /cost: Retrieve Cost Estimate
🔧 Drivers (1 endpoints)
• GET /drivers: List Nearby Drivers
🔧 Eta (1 endpoints)
• GET /eta: Retrieve Pickup ETA
🔧 Profile (1 endpoints)
• GET /profile: Retrieve User Profile
🔧 Rides (7 endpoints)
• GET /rides: Update Sandbox Ride Status • POST /rides: Request a Lyft • GET /rides/{id}: Get the ride detail of a given ride ID • POST /rides/{id}/cancel: Cancel a ongoing requested ride • PUT /rides/{id}/destination: Update the destination of the ride • PUT /rides/{id}/rating: Add the passenger's rating, feedback, and tip • GET /rides/{id}/receipt: Get the receipt of the rides.
🔧 Ridetypes (1 endpoints)
• GET /ridetypes: Update Driver Availability
🔧 Sandbox (4 endpoints)
• PUT /sandbox/primetime: Set Prime Time Percentage • PUT /sandbox/rides/{id}: Propagate ride through ride status • PUT /sandbox/ridetypes: Preset types of rides for sandbox • PUT /sandbox/ridetypes/{ride_type}: Driver availability for processing ride request
🤖 AI Integration
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 Lyft API responses with full data structure
Error Handling: Built-in n8n HTTP request error management
💡 Usage Examples
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
✨ Benefits
• 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.
n8n MCP Server Trigger Workflow
This n8n workflow demonstrates a basic setup using the Model Context Protocol (MCP) Server Trigger. It serves as a foundational template for building AI agent integrations, allowing external AI agents to initiate workflows and interact with n8n.
What it does
This workflow contains a single node:
- MCP Server Trigger: This node acts as an entry point for AI agents or other external systems that communicate using the Model Context Protocol. When an MCP message is received, this node triggers the workflow.
Prerequisites/Requirements
- n8n Instance: An active n8n instance where this workflow can be imported and run.
- Model Context Protocol (MCP) Client: An external AI agent or system capable of sending requests formatted according to the Model Context Protocol to the n8n instance's MCP endpoint.
Setup/Usage
- Import the workflow: Download the provided JSON and import it into your n8n instance.
- Activate the workflow: After importing, ensure the workflow is activated to start listening for incoming MCP requests.
- Configure your MCP Client: Point your AI agent or MCP client to the URL of your n8n instance's MCP endpoint (typically
YOUR_N8N_URL/webhook-test/mcp). - Send a request: Your MCP client can now send requests to this endpoint, which will trigger the workflow.
This workflow is a starting point. You would typically extend it by adding more nodes after the MCP Server Trigger to process the incoming data, interact with other services (like Lyft, as hinted by the directory name, although not present in this specific JSON), and return responses to the AI agent.
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