BlaBlaCar MCP Server for LangChain 8 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect BlaBlaCar 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({
"blablacar": {
"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 BlaBlaCar, 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 BlaBlaCar MCP Server
What you can do
Connect AI agents to the world's largest carpooling network for affordable, sustainable travel:
LangChain's ecosystem of 500+ components combines seamlessly with BlaBlaCar through native MCP adapters. Connect 8 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.
- Search carpool rides between any cities or GPS coordinates worldwide
- Compare prices and schedules across multiple drivers and departure times
- Review driver profiles with ratings, verification status, and vehicle details
- Find bus trips on BlaBlaCar Bus routes for longer distances
- Search with flexible dates to find cheapest travel days
- International rides across borders with country-specific filtering
- Radius-based searches for flexible pickup location options
The BlaBlaCar MCP Server exposes 8 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 BlaBlaCar to LangChain via MCP
Follow these steps to integrate the BlaBlaCar 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 8 tools from BlaBlaCar via MCP
Why Use LangChain with the BlaBlaCar MCP Server
LangChain provides unique advantages when paired with BlaBlaCar through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine BlaBlaCar 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 BlaBlaCar queries for multi-turn workflows
BlaBlaCar + LangChain Use Cases
Practical scenarios where LangChain combined with the BlaBlaCar MCP Server delivers measurable value.
RAG with live data: combine BlaBlaCar tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query BlaBlaCar, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain BlaBlaCar tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every BlaBlaCar tool call, measure latency, and optimize your agent's performance
BlaBlaCar MCP Tools for LangChain (8)
These 8 tools become available when you connect BlaBlaCar to LangChain via MCP:
get_driver_profile
Use this to verify driver credibility and read passenger reviews before booking a ride. Requires the driver user ID from a trip result. Get driver profile and ratings on BlaBlaCar
get_trip_details
Use this before booking to verify driver credibility, vehicle comfort, and exact pickup location. Get complete details of a specific BlaBlaCar trip including driver and vehicle info
search_bus_trips
BlaBlaCar operates both carpooling and bus services. Bus trips are operated by professional drivers on fixed routes. Returns bus departure/arrival times, prices, and availability. Use this for longer distance or when carpool options are limited. Search BlaBlaCar Bus trips between two locations
search_flexible_dates
Much larger result set than exact-date search. Useful when travel dates are not fixed and user wants to compare prices/availability across multiple days. Returns up to 50 results spanning several days. Search carpool trips with flexible dates around a target date
search_international_trips
Requires origin/destination coordinates plus country codes (e.g., FR, DE, ES, IT, PT). Returns all available international rides with driver details and pricing. Use this for trips crossing national borders. Search international carpool trips between two countries on BlaBlaCar
search_trips
Requires latitude,longitude format for both points. Returns trip details including departure/arrival cities, times, price, driver info, and available seats. Use this for precise location-based searches when you know exact coordinates. Search carpool trips between two GPS coordinates on BlaBlaCar
search_trips_by_city
More user-friendly than coordinate-based search. Returns all matching trips with departure/arrival points, times, prices, driver ratings, and available seats. Best for general city-to-city searches without needing exact coordinates. Search carpool trips between two city names on BlaBlaCar
search_trips_with_radius
Useful when exact pickup/dropoff locations are flexible. Larger radius returns more options but may require additional travel to reach departure points. Returns all rides within the specified radius. Search carpool trips with flexible radius around coordinates
Example Prompts for BlaBlaCar in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with BlaBlaCar immediately.
"Find carpool rides from Paris to Lyon next Friday for 2 people"
"What's the cheapest day to travel from São Paulo to Rio next week?"
"Show me both carpool and bus options from Madrid to Barcelona this weekend"
Troubleshooting BlaBlaCar MCP Server with LangChain
Common issues when connecting BlaBlaCar to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersBlaBlaCar + LangChain FAQ
Common questions about integrating BlaBlaCar 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 BlaBlaCar with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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Anthropic's agentic CLI for terminal-first development.
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Google's framework for building production AI agents.
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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 BlaBlaCar to LangChain
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.