Lyft MCP Server for OpenAI Agents SDK 9 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Lyft through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MCPServerStreamableHttp(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as mcp_server:
agent = Agent(
name="Lyft Assistant",
instructions=(
"You help users interact with Lyft. "
"You have access to 9 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Lyft"
)
print(result.final_output)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Lyft MCP Server
What you can do
Connect AI agents to the Lyft platform for complete ride automation:
The OpenAI Agents SDK auto-discovers all 9 tools from Lyft through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Lyft, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
- Get available ride types (Lyft, XL, Lux) at any location
- Estimate ride costs across all products before booking
- Compare pickup ETAs to choose the fastest option
- Request rides directly with origin and destination coordinates
- Track active rides with driver info, vehicle details, and real-time status
- Cancel rides when plans change
- View complete ride history with pricing and route data
- Save favorite locations (Home, Work, custom places)
The Lyft MCP Server exposes 9 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Lyft to OpenAI Agents SDK via MCP
Follow these steps to integrate the Lyft MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 9 tools from Lyft
Why Use OpenAI Agents SDK with the Lyft MCP Server
OpenAI Agents SDK provides unique advantages when paired with Lyft through the Model Context Protocol.
Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety
Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure
Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate
First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output
Lyft + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Lyft MCP Server delivers measurable value.
Automated workflows: build agents that query Lyft, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Lyft, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Lyft tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Lyft to resolve tickets, look up records, and update statuses without human intervention
Lyft MCP Tools for OpenAI Agents SDK (9)
These 9 tools become available when you connect Lyft to OpenAI Agents SDK via MCP:
cancel_ride
Cancellation policies vary based on ride status - cancellations after driver assignment may incur fees. Use this to cancel rides that were booked by mistake or are no longer needed. Cancel an existing Lyft ride request
get_cost_estimate
Prices are in local currency (USD). Use this to compare costs across different Lyft products before booking. Get cost estimate for a Lyft ride between two locations
get_eta_estimate
Use this to compare how quickly different Lyft services can reach you. Lower minutes mean faster pickups. Get estimated arrival times for Lyft at a location
get_locations
Returns location IDs, names, addresses, and coordinates. Use this to quickly reference saved locations for ride requests without typing full addresses. Get saved locations for the Lyft account
get_ride_details
Use this to track your active ride or review past ride details. Get details of a specific Lyft ride
get_ride_history
Returns ride date, status, origin/destination, ride type, driver, and cost. Use this to review past rides, calculate expenses, or find previous trip details. Get ride history for the authenticated Lyft account
get_ride_types
) available at the specified latitude/longitude. Returns ride type IDs, display names, capacity, and descriptions. Use this to see which ride options are available before requesting price or time estimates. Get available Lyft ride types at a location
request_ride
Requires ride type ID (from get_ride_types), origin coordinates, and destination coordinates. Optionally include pickup/dropoff addresses for clarity. Returns the ride ID and status. Use this to book a ride after confirming price and availability. Request a new Lyft ride
set_location
Requires location ID, latitude, and longitude. Optionally include a display name. The location ID can be home, work, or any custom string. Returns the saved location details. Use this to manage your favorite pickup/dropoff spots. Save or update a location for the Lyft account
Example Prompts for Lyft in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Lyft immediately.
"Get me a price estimate from JFK Airport to Times Square for a Lyft XL"
"Book me a Lyft from my home to San Francisco International Airport"
"Show me my last 20 Lyft rides and total spending"
Troubleshooting Lyft MCP Server with OpenAI Agents SDK
Common issues when connecting Lyft to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Lyft + OpenAI Agents SDK FAQ
Common questions about integrating Lyft MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect Lyft with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Lyft to OpenAI Agents SDK
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.