How to Use the Meituan Waimai MCP in OpenAI Agents SDK

Q: How do I integrate Meituan Waimai with my OpenAI Agents SDK project?

You connect the server by initializing an MCPServerStreamableHttp instance with your endpoint. Pass this object into your Agent constructor's mcpservers list to grant your agent direct access to all available tools.

Q: Can my OpenAI Agents SDK agent handle high-volume Meituan Waimai orders?

Yes, but you should set cacheToolsList=True to improve performance. This prevents the agent from re-fetching tool definitions on every turn, keeping the communication snappy during busy periods.

Q: Does the Meituan Waimai MCP Server support automatic order confirmation in OpenAI Agents SDK?

You can write a custom agent flow that triggers confirmorder as soon as a new order appears in the getorderlist response. Your agent performs the logic, and the server executes the API call.

Q: How do I manage inventory for Meituan Waimai using OpenAI Agents SDK?

Use the updatestock tool to modify quantities for any foodid identified via listmenus. You can build a loop that monitors stock levels and triggers updates automatically when levels drop.

Manage food delivery operations directly within your OpenAI Agents SDK agent using this MCP Server.

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Connect Meituan Waimai MCP to OpenAI Agents SDK

Create your Vinkius account to connect Meituan Waimai 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 Meituan Waimai with OpenAI Agents SDK

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Claude

Perplexity

Full order lifecycle management

Control the entire fulfillment flow by using `confirm_order` to start preparation and `mark_delivering` to notify customers of progress. This lets your agent handle incoming requests without manual oversight. Finalize transactions using `complete_order` once the food is handed off, ensuring payouts trigger immediately. Your agent maintains state consistency across every delivery.

Dynamic menu and inventory control

Keep your storefront accurate by calling `list_menus` to pull current items and `update_stock` to hide unavailable dishes. This prevents customer frustration when ingredients run out. Automate your inventory updates so the menu reflects reality in real-time. Your agent handles the logic, keeping your restaurant data clean and reliable.

Proactive customer service automation

Address complaints faster by using `get_order_detail` to verify order status and `handle_refund` to resolve payment issues. Your agent acts on specific order IDs to fix problems before they escalate. Process refund requests based on clear evidence from the order history. This keeps your operations moving while maintaining trust with your customers.

Setup guide

Set up Meituan Waimai 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 Meituan Waimai tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Meituan Waimai 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="Meituan Waimai Agent",
            instructions="You have access to Meituan Waimai 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 Meituan Waimai. 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 Meituan Waimai MCP in OpenAI Agents SDK

You connect the server by initializing an `MCPServerStreamableHttp` instance with your endpoint. Pass this object into your Agent constructor's `mcp_servers` list to grant your agent direct access to all available tools.

Yes, but you should set `cacheToolsList=True` to improve performance. This prevents the agent from re-fetching tool definitions on every turn, keeping the communication snappy during busy periods.

You can write a custom agent flow that triggers `confirm_order` as soon as a new order appears in the `get_order_list` response. Your agent performs the logic, and the server executes the API call.

Use the `update_stock` tool to modify quantities for any `food_id` identified via `list_menus`. You can build a loop that monitors stock levels and triggers updates automatically when levels drop.

The server treats your order data as ephemeral, meaning it doesn't store sensitive customer information locally. All interactions occur over an authenticated connection, ensuring only your agent can access private order details.

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