Do I need a Cabify Business account to use this MCP?

Yes, this MCP server requires a Cabify Empresas (Business) account with API access. Individual consumer accounts do not have API credentials. If your company uses Cabify for corporate transportation, contact your admin to request API access from the Cabify Empresas portal.

Which cities and countries does Cabify operate in?

Cabify operates primarily in Spain (Madrid, Barcelona, Valencia, Seville), Portugal (Lisbon, Porto), and Latin America (Mexico, Colombia, Chile, Argentina, Peru, Uruguay, Panama, Costa Rica). Service availability and product types vary by city. Check coverage at cabify.com for your specific location.

Can this MCP integrate with expense management systems like Concur?

The Cabify Business API supports integration with expense platforms like SAP Concur. The ride history tool returns structured expense data including cost breakdowns, business categories, and receipts. Your company's Cabify admin can configure Concur sync directly in the Cabify Empresas portal for automated expense reporting.

Cabify MCP Server for CrewAI 9 tools — connect in under 2 minutes

Name: Cabify
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 9 Tools Framework

Connect your CrewAI agents to Cabify through Vinkius, pass the Edge URL in the `mcps` parameter and every Cabify tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Cabify Specialist",
    goal="Help users interact with Cabify effectively",
    backstory=(
        "You are an expert at leveraging Cabify tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Cabify "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 9 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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* 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:

When paired with CrewAI, Cabify becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Cabify tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the Cabify MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 9 tools from Cabify

Why Use CrewAI with the Cabify MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Cabify through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Cabify + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Cabify MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Cabify for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Cabify, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Cabify tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Cabify against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Cabify MCP Tools for CrewAI (9)

These 9 tools become available when you connect Cabify to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

Common issues when connecting Cabify to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Cabify + CrewAI FAQ

Common questions about integrating Cabify MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.