Cabify MCP Server for LangChain 9 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Cabify through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
async with MultiServerMCPClient({
"cabify": {
"transport": "streamable_http",
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
}
}) as client:
tools = client.get_tools()
agent = create_react_agent(
ChatOpenAI(model="gpt-4o"),
tools,
)
response = await agent.ainvoke({
"messages": [{
"role": "user",
"content": "Using Cabify, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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:
LangChain's ecosystem of 500+ components combines seamlessly with Cabify through native MCP adapters. Connect 9 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.
- 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 LangChain 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 LangChain via MCP
Follow these steps to integrate the Cabify MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 9 tools from Cabify via MCP
Why Use LangChain with the Cabify MCP Server
LangChain provides unique advantages when paired with Cabify through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Cabify MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Cabify queries for multi-turn workflows
Cabify + LangChain Use Cases
Practical scenarios where LangChain combined with the Cabify MCP Server delivers measurable value.
RAG with live data: combine Cabify tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Cabify, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Cabify tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Cabify tool call, measure latency, and optimize your agent's performance
Cabify MCP Tools for LangChain (9)
These 9 tools become available when you connect Cabify to LangChain 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 LangChain
Ready-to-use prompts you can give your LangChain 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 LangChain
Common issues when connecting Cabify to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersCabify + LangChain FAQ
Common questions about integrating Cabify MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
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 LangChain
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.