Cabify 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 Cabify 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="Cabify Assistant",
instructions=(
"You help users interact with Cabify. "
"You have access to 9 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Cabify"
)
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 Cabify MCP Server
What you can do
Connect AI agents to the Cabify Business platform for enterprise mobility management:
The OpenAI Agents SDK auto-discovers all 9 tools from Cabify through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Cabify, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
- Get price estimates across all Cabify tiers (Lite, Executive, Taxi)
- Compare trip durations with real-time traffic data
- Request rides directly with pickup and dropoff coordinates
- Track active rides with driver info, vehicle details, and live ETA
- Cancel rides when plans change
- View complete ride history with business expense tracking
- Manage saved locations for frequent business destinations
- Check available service tiers at any location in Spain and LATAM
The Cabify 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 Cabify to OpenAI Agents SDK via MCP
Follow these steps to integrate the Cabify 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 Cabify
Why Use OpenAI Agents SDK with the Cabify MCP Server
OpenAI Agents SDK provides unique advantages when paired with Cabify 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
Cabify + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Cabify MCP Server delivers measurable value.
Automated workflows: build agents that query Cabify, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Cabify, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Cabify tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Cabify to resolve tickets, look up records, and update statuses without human intervention
Cabify MCP Tools for OpenAI Agents SDK (9)
These 9 tools become available when you connect Cabify to OpenAI Agents SDK via MCP:
add_saved_location
Common use cases: save office addresses, frequent client locations, hotels, airports. Returns the saved location details including the new location ID. Use this to build a library of frequently used destinations for faster ride booking. Save a new location for the Cabify account
cancel_ride
Cancellation policies vary based on ride status - cancellations after driver assignment may incur fees depending on Cabify Empresas policy. Use this to cancel rides that were booked by mistake or are no longer needed. Cancel an existing Cabify ride request
get_available_products
Returns product IDs, names, descriptions, capacity, and features. Use this to see which service options are available before requesting estimates or booking rides. Get available Cabify service tiers at a location
get_price_estimate
Prices are in local currency (EUR for Spain, local currency for LATAM). Use this to compare costs across different Cabify service tiers before booking. Get price estimate for a Cabify ride between two locations
get_ride_details
Use this to track your active ride or review past trip details. Get details of a specific Cabify ride
get_ride_history
Returns ride date, status, origin/destination, product type, driver, cost, and business expense category. Use this to review past rides, calculate business expenses, or find previous trip details. Get ride history for the Cabify Business account
get_saved_locations
Returns location IDs, names, addresses, and coordinates. Use this to quickly reference saved locations for ride requests without typing full addresses. Common for frequent business destinations. Get saved locations for the Cabify account
get_time_estimate
Accounts for current traffic conditions and typical route times. Use this to plan schedules and compare route efficiency across different pickup/dropoff points. Get estimated trip duration for a Cabify ride
request_ride
Requires origin and destination coordinates. Optionally specify product ID (from get_available_products), pickup address, and dropoff address for clarity. Returns the ride ID, driver assignment status, and estimated pickup time. Use this to book a ride after confirming price and availability. Request a new Cabify ride
Example Prompts for Cabify in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Cabify immediately.
"Get me a price estimate from Madrid Airport to our office in Gran Vía for a Cabify Executive"
"Book a Cabify from the hotel to the conference center for 9am tomorrow"
"Show me all Cabify rides from last month with total business expenses"
Troubleshooting Cabify MCP Server with OpenAI Agents SDK
Common issues when connecting Cabify to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Cabify + OpenAI Agents SDK FAQ
Common questions about integrating Cabify 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 Cabify 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 Cabify to OpenAI Agents SDK
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.