BlaBlaCar MCP Server for OpenAI Agents SDK 8 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect BlaBlaCar 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="BlaBlaCar Assistant",
instructions=(
"You help users interact with BlaBlaCar. "
"You have access to 8 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from BlaBlaCar"
)
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 BlaBlaCar MCP Server
What you can do
Connect AI agents to the world's largest carpooling network for affordable, sustainable travel:
The OpenAI Agents SDK auto-discovers all 8 tools from BlaBlaCar through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries BlaBlaCar, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
- 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 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 BlaBlaCar to OpenAI Agents SDK via MCP
Follow these steps to integrate the BlaBlaCar 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 8 tools from BlaBlaCar
Why Use OpenAI Agents SDK with the BlaBlaCar MCP Server
OpenAI Agents SDK provides unique advantages when paired with BlaBlaCar 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
BlaBlaCar + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the BlaBlaCar MCP Server delivers measurable value.
Automated workflows: build agents that query BlaBlaCar, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries BlaBlaCar, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through BlaBlaCar tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query BlaBlaCar to resolve tickets, look up records, and update statuses without human intervention
BlaBlaCar MCP Tools for OpenAI Agents SDK (8)
These 8 tools become available when you connect BlaBlaCar to OpenAI Agents SDK 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 OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK 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 OpenAI Agents SDK
Common issues when connecting BlaBlaCar to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
BlaBlaCar + OpenAI Agents SDK FAQ
Common questions about integrating BlaBlaCar 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 BlaBlaCar 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 BlaBlaCar to OpenAI Agents SDK
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.