How to Use the Foodpanda MCP in OpenAI Agents SDK

Q: How do I connect the Foodpanda MCP Server to the OpenAI Agents SDK?

Install openai-agents via pip. Initialize MCPServerStreamableHttp with your Vinkius endpoint URL and pass it to your agent's mcpservers list. Set cacheToolsList=True to speed up tool discovery.

Q: Can OpenAI Agents SDK handle asynchronous Foodpanda updates?

Yes. Your agent can dispatch catalog changes and then poll getcatalogjob to confirm success. The SDK's async context manager handles the wait states without blocking your main event loop.

Q: Does the Foodpanda integration support multi-agent handoffs in OpenAI Agents SDK?

It does. You can assign getorderhistory to an analytics agent and updatevendorstatus to an operations agent. The framework routes the tasks to the right specialist automatically.

Q: How does this setup protect Foodpanda customer order data?

The getorderdetails tool processes customer addresses and phone numbers inside an ephemeral V8 Isolate Sandbox. Vinkius drops the container the millisecond the request finishes. Zero persistent storage means zero data leaks.

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Connect Foodpanda MCP to OpenAI Agents SDK

Create your Vinkius account to connect Foodpanda 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 Foodpanda with OpenAI Agents SDK

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Track and update orders via MCP Server

The `get_order_details` and `get_order_history` tools let your OpenAI agent read active delivery states directly from the Foodpanda API. This means your customer support bot can verify a missing item claim before issuing a refund. You can write back to the platform using `update_order`. If an agent detects a kitchen delay, it triggers the update tool and adjusts the estimated delivery time. Handoffs between specialized agents handle the read-write cycle safely.

Automate menu pricing and promotions

The `upsert_promotion` tool gives your agent direct control over discount campaigns. You set the guardrails in the OpenAI Agents SDK, and the agent applies flash sales when inventory runs high. Managing the actual items requires `add_catalog_products` and `update_vendor_catalog`. Your system checks local stock levels and pushes exact menu changes to the Foodpanda storefront. You track the async backend work using `get_promotion_job` and `get_catalog_job`.

Control store availability dynamically

The `get_vendor_status` tool tells your agent if a specific restaurant location is currently open, closed, or busy. This prevents your system from routing orders to an overwhelmed kitchen. When the rush hits, your agent calls `update_vendor_status` to pause incoming requests. Built-in tracing in the OpenAI dashboard logs exactly when and why the agent flipped the switch.

Setup guide

Set up Foodpanda 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 Foodpanda tools at runtime.
3

Create your Agent

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

Run the agent

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

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Foodpanda. 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.

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Common questions about Foodpanda MCP in OpenAI Agents SDK

Install `openai-agents` via pip. Initialize `MCPServerStreamableHttp` with your Vinkius endpoint URL and pass it to your agent's `mcp_servers` list. Set `cacheToolsList=True` to speed up tool discovery.

Yes. Your agent can dispatch catalog changes and then poll `get_catalog_job` to confirm success. The SDK's async context manager handles the wait states without blocking your main event loop.

It does. You can assign `get_order_history` to an analytics agent and `update_vendor_status` to an operations agent. The framework routes the tasks to the right specialist automatically.

OpenAI's built-in guardrails catch malformed requests before they hit the server. You define the validation rules, and the agent corrects its own payload before calling `update_vendor_catalog`.

The `get_order_details` tool processes customer addresses and phone numbers inside an ephemeral V8 Isolate Sandbox. Vinkius drops the container the millisecond the request finishes. Zero persistent storage means zero data leaks.

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