How do I get my Meituan Waimai App ID and App Secret?

Log in to the [Meituan Waimai Developer Console](https://developer.waimai.meituan.com/), navigate to **API Documentation** > **Access Guide**, and register your application. You'll receive an App ID and App Secret. Make sure your application has the required API permissions for order management, menu access, and refund handling. The signature algorithm uses MD5 hashing of sorted parameters combined with your App Secret.

What's the order lifecycle in Meituan Waimai?

The typical order flow is: **1) Pending (待确认, status=1)** — Customer placed order, awaiting merchant confirmation. **2) Confirmed (已确认, status=3)** — Merchant accepted the order, kitchen starts preparation. **3) Delivering (配送中, status=5)** — Food is out for delivery with rider. **4) Completed (已完成, status=7)** — Customer received the order, payment settled. **5) Cancelled (已取消, status=8)** — Order was cancelled by merchant or customer. At each stage, you can query details, and merchants can con

How do I handle stock management and sold-out items?

Use the `update_stock` tool to set stock quantities for menu items. Set `stock=0` to mark an item as sold out (it will immediately disappear from the customer menu). Set a positive number to replenish stock. Get the food ID from the `list_menus` tool first. This is critical during peak hours when ingredients run out — quickly updating stock prevents customers from ordering unavailable items and reduces refund requests.

Meituan Waimai MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Meituan Waimai
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Meituan Waimai through the Vinkius — pass the Edge URL in the `mcps` parameter and every Meituan Waimai tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Meituan Waimai Specialist",
    goal="Help users interact with Meituan Waimai effectively",
    backstory=(
        "You are an expert at leveraging Meituan Waimai tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Meituan Waimai "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Meituan Waimai MCP Server

Connect your Meituan Waimai (美团外卖) restaurant operations to any AI agent and transform your delivery management through natural conversation. Meituan Waimai is China's largest food delivery platform, handling millions of daily orders across hundreds of thousands of restaurants.

When paired with CrewAI, Meituan Waimai becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Meituan Waimai tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

What you can do

Order Management — Retrieve detailed order information, list orders by status (pending, confirmed, delivering, completed, cancelled)
Order Lifecycle Control — Confirm new orders, mark orders as delivering, complete deliveries, or cancel with explanations
Refund Processing — Approve or reject customer refund requests with detailed reasoning and order verification
Restaurant Information — Query restaurant details including ratings, addresses, business hours, and delivery coverage
Menu Management — List full restaurant catalogs, filter by category, view prices, descriptions, and stock levels
Stock Control — Update item availability in real-time, mark items as sold out, or replenish inventory
Delivery Tracking — Mark orders as out for delivery with rider information for customer transparency

The Meituan Waimai MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI 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 Meituan Waimai to CrewAI via MCP

Follow these steps to integrate the Meituan Waimai MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 10 tools from Meituan Waimai

Why Use CrewAI with the Meituan Waimai MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Meituan Waimai through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Meituan Waimai + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Meituan Waimai MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Meituan Waimai for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Meituan Waimai, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Meituan Waimai tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Meituan Waimai against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Meituan Waimai MCP Tools for CrewAI (10)

These 10 tools become available when you connect Meituan Waimai to CrewAI via MCP:

cancel_order

Requires a cancellation reason explaining why the order is being cancelled (e.g., "restaurant closed", "item out of stock", "unable to prepare"). The order must be in a cancellable state (not already completed or delivered). Use carefully as cancellations impact merchant ratings and customer experience. Cancel a Meituan delivery order with a reason

complete_order

This is the final state in the order lifecycle and indicates the customer has received their food. Should only be called after the delivery rider has confirmed drop-off or the customer has picked up the order. Triggers payment settlement to the merchant. Mark a Meituan delivery order as completed

confirm_order

This transitions the order to confirmed status and begins the preparation workflow. Required step before marking the order as delivering. Use the order ID from the order list and the restaurant POI ID. Essential for acknowledging new orders and starting the fulfillment process. Confirm a pending Meituan delivery order

get_order_detail

Use the order ID obtained from the order list to track specific orders, verify order contents, check delivery addresses, or investigate customer complaints. Essential for order management and customer service operations. Get detailed information about a specific Meituan delivery order

get_order_list

Filter by order status: 1=待确认 (pending confirmation), 3=已确认 (confirmed), 5=配送中 (delivering), 7=已完成 (completed), 8=已取消 (cancelled). Pagination uses page number and limit parameters. Critical for monitoring incoming orders, tracking order volume, and managing the order pipeline. List orders for a Meituan restaurant with optional status filter

get_restaurant_info

Use the POI ID (Point of Interest identifier) to get restaurant details before managing orders, verifying delivery coverage, or checking business hours. Essential for multi-restaurant operators managing multiple POIs. Get detailed information about a Meituan restaurant/POI

handle_refund

When rejecting, provide a reason explaining the refusal. Refund requests typically come with customer explanations and evidence. Use order details to verify the claim before making a decision. Approved refunds are processed back to the customer's original payment method. Approve or reject a refund request for a Meituan order

list_menus

Optionally filter by category ID to get items from a specific menu section (e.g., appetizers, mains, drinks). Critical for inventory management, price updates, and menu optimization. Returns stock quantities to help identify low-stock items. List menu items for a Meituan restaurant

mark_delivering

Optionally includes delivery rider name and phone number for customer tracking. Use this for self-delivery orders where the restaurant manages their own riders. For Meituan-managed delivery, the platform handles this automatically. Mark a Meituan order as being delivered (out for delivery)

update_stock

Use this to mark items as sold out (stock=0) when ingredients run out, or replenish stock when new inventory arrives. Stock changes immediately reflect on the customer-facing menu. Essential for preventing orders for unavailable items and maintaining accurate inventory. Food ID is obtained from the list_menus tool. Update stock quantity for a menu item in Meituan

Example Prompts for Meituan Waimai in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with Meituan Waimai immediately.

"Show me all pending orders for my restaurant POI123."

"Mark food ID 4567 as sold out for POI123 — we ran out of chicken."

"Handle refund request for order ORD-789 — customer says food never arrived. Approve it."

Troubleshooting Meituan Waimai MCP Server with CrewAI

Common issues when connecting Meituan Waimai to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Meituan Waimai + CrewAI FAQ

Common questions about integrating Meituan Waimai MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.