How to Use the Pando MCP in OpenAI Agents SDK

Q: What happens if a carrier API times out during a query?

Your agent can run checkapistatus to verify the connection health. If the endpoint is down, the SDK handles the exception gracefully, allowing your agent to retry or alert a dispatcher.

Run automated freight dispatch and carrier matching directly inside your OpenAI Agents SDK workflows.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Pando MCP to OpenAI Agents SDK

Create your Vinkius account to connect Pando to OpenAI Agents SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

GDPR Included with Plan

Setup Pando with OpenAI Agents SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity Vinkius runs on Gemini

Gemini

Grok

Automate vehicle indents with OpenAI Agents SDK

The `create_indent` tool lets your OpenAI agent generate new freight indents directly within your Python execution loop using the MCP Server. By feeding raw customer requests to your agent, the system books transport vehicles without requiring manual data entry. Your agent uses `check_api_status` to confirm the logistics network is active before running any booking operations. This setup prevents failed API calls from disrupting your automated shipping pipeline.

Real-time carrier filtering and route optimization

The `list_carriers` tool gives your Python agents immediate access to your approved transport partners. Instead of scrolling through spreadsheets, your agent queries active carriers to find the best match for a specific route. Combining this with `list_routes` allows the OpenAI framework to calculate optimal paths based on historical transit data. You get faster carrier assignments because the agent handles the comparison logic locally.

End-to-end shipment tracking and status updates

The `get_shipment_details` tool pulls live status updates via the MCP connection for any active freight run directly into your agent's context. Your agent monitors these details to flag delayed trucks or missing documentation automatically. Using `list_shipments` alongside your agent's reasoning capabilities lets you build automated daily digest reports. This eliminates the need for manual check-calls to dispatchers.

Setup guide

Set up Pando 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 Pando tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Pando 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="Pando Agent",
            instructions="You have access to Pando tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Pando. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Pando now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Pando MCP in OpenAI Agents SDK

You register the MCP Server directly in your Python code using the streamable HTTP parameters. Once connected, your OpenAI agents auto-discover the tools and can trigger `create_indent` based on user prompts.

Yes, you control tool exposure during the agent initialization phase in Python. By limiting the tool list, you prevent autonomous agents from accidentally triggering `create_indent` or viewing sensitive carrier lists.

The SDK lets you define validation hooks that intercept tool calls before they execute. If an agent tries to run `create_indent` with an invalid carrier ID, your pre-execution check halts the action.

Your agent can run `check_api_status` to verify the connection health. If the endpoint is down, the SDK handles the exception gracefully, allowing your agent to retry or alert a dispatcher.

All data passing through the MCP Server is isolated within a zero-trust V8 sandbox. Your freight indents and carrier contracts never persist on external servers, keeping your supply chain logs completely private.

Use it with your favorite AI tools

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

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript