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

Built by Vinkius GDPR 9 Tools Framework

LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Cabify as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.

Vinkius supports streamable HTTP and SSE.

python
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        tools=tools,
        llm=OpenAI(model="gpt-4o"),
        system_prompt=(
            "You are an assistant with access to Cabify. "
            "You have 9 tools available."
        ),
    )

    response = await agent.run(
        "What tools are available in Cabify?"
    )
    print(response)

asyncio.run(main())
Cabify
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About Cabify MCP Server

What you can do

Connect AI agents to the Cabify Business platform for enterprise mobility management:

LlamaIndex agents combine Cabify tool responses with indexed documents for comprehensive, grounded answers. Connect 9 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.

  • 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 LlamaIndex 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 LlamaIndex via MCP

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

01

Install dependencies

Run pip install llama-index-tools-mcp llama-index-llms-openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the agent

Save to agent.py and run: python agent.py

04

Explore tools

The agent discovers 9 tools from Cabify

Why Use LlamaIndex with the Cabify MCP Server

LlamaIndex provides unique advantages when paired with Cabify through the Model Context Protocol.

01

Data-first architecture: LlamaIndex agents combine Cabify tool responses with indexed documents for comprehensive, grounded answers

02

Query pipeline framework lets you chain Cabify tool calls with transformations, filters, and re-rankers in a typed pipeline

03

Multi-source reasoning: agents can query Cabify, a vector store, and a SQL database in a single turn and synthesize results

04

Observability integrations show exactly what Cabify tools were called, what data was returned, and how it influenced the final answer

Cabify + LlamaIndex Use Cases

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

01

Hybrid search: combine Cabify real-time data with embedded document indexes for answers that are both current and comprehensive

02

Data enrichment: query Cabify to augment indexed data with live information before generating user-facing responses

03

Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Cabify for fresh data

04

Analytical workflows: chain Cabify queries with LlamaIndex's data connectors to build multi-source analytical reports

Cabify MCP Tools for LlamaIndex (9)

These 9 tools become available when you connect Cabify to LlamaIndex via MCP:

01

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

02

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

03

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

04

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

05

get_ride_details

Use this to track your active ride or review past trip details. Get details of a specific Cabify ride

06

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

07

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

08

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

09

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 LlamaIndex

Ready-to-use prompts you can give your LlamaIndex agent to start working with Cabify immediately.

01

"Get me a price estimate from Madrid Airport to our office in Gran Vía for a Cabify Executive"

02

"Book a Cabify from the hotel to the conference center for 9am tomorrow"

03

"Show me all Cabify rides from last month with total business expenses"

Troubleshooting Cabify MCP Server with LlamaIndex

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

01

BasicMCPClient not found

Install: pip install llama-index-tools-mcp

Cabify + LlamaIndex FAQ

Common questions about integrating Cabify MCP Server with LlamaIndex.

01

How does LlamaIndex connect to MCP servers?

Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
02

Can I combine MCP tools with vector stores?

Yes. LlamaIndex agents can query Cabify tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
03

Does LlamaIndex support async MCP calls?

Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.

Connect Cabify to LlamaIndex

Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.