Complete Lyft API integration for AI agents with 16 operations using MCP

Need help? Want access to this workflow + many more paid workflows + live Q&A sessions with a top verified n8n creator?

Join the community

Complete MCP server exposing 16 Lyft API operations to AI agents.

⚡ Quick Setup

1. Import this workflow into your n8n instance
2. Credentials Add Lyft credentials
3. Activate the workflow to start your MCP server
4. Copy the webhook URL from the MCP trigger node
5. 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.