How to Use the BlaBlaCar MCP in OpenAI Agents SDK

Book rides directly through your OpenAI Agents SDK agent using this BlaBlaCar MCP Server.

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Connect BlaBlaCar MCP to OpenAI Agents SDK

Create your Vinkius account to connect BlaBlaCar to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup BlaBlaCar with OpenAI Agents SDK

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Find rides with OpenAI Agents SDK

Your agent queries `search_trips_by_city` to pull current carpool availability between your chosen locations. It parses the return data to show you the best price and seat count. Once you pick a ride, use `get_trip_details` to verify the pickup spot and vehicle comfort. The agent handles the lookup without you leaving your Python codebase.

Check driver history automatically

Before you commit to a travel plan, the agent invokes `get_driver_profile` using the ID from your search results. It pulls the driver's rating and past feedback directly into your context. You get a clear view of who you are riding with before any booking happens. This keeps your travel plans safe and transparent.

Manage long-distance travel

For journeys crossing borders, the agent calls `search_international_trips` to get accurate pricing and schedule info. It handles the coordinate math so you don't have to. Use `search_bus_trips` when you need a fixed-route option for longer hauls. This MCP Server gives your agent full access to both carpool and bus inventory.

Setup guide

Set up BlaBlaCar MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all BlaBlaCar tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives BlaBlaCar tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate BlaBlaCar tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="BlaBlaCar Agent",
            instructions="You have access to BlaBlaCar tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

Get your connection token →

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Common questions about BlaBlaCar MCP in OpenAI Agents SDK

Yes. Your agent uses the toolset to request specific criteria like city names or coordinates. You can write custom logic to narrow down the returned trip list based on your own preferences.

Install the necessary packages and instantiate the MCPServerStreamableHttp class with your Vinkius endpoint. Pass this server object into your Agent constructor to enable tool discovery.

You only need to provide your endpoint token during the server configuration. The Vinkius platform handles the authentication layer so your code stays focused on booking rides.

The tools fetch live data from the provider for every request. You will see exactly how many seats are left at the moment your agent executes the search.

This server only processes public trip info, driver ratings, and vehicle details. It does not store your private account credentials or payment history on our servers.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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