How to Use the Foodpanda MCP in AutoGen

Q: How do I load Foodpanda tools into AutoGen?

Use the autogen-extmcp package. Initialize mcpservertools with your Vinkius HTTP transport parameters, and pass the resulting list directly to your AssistantAgent constructor.

Q: Can AutoGen agents safely manage Foodpanda promotions?

Yes. You assign upsertpromotion to a specific agent and require approval from a secondary reviewer agent before the system executes the tool.

Q: How do the agents know if an MCP Server bulk upload worked?

The executing agent calls addcatalogproducts and receives a job ID. It then loops getcatalogjob until the platform confirms the task finished.

Q: Do these Foodpanda tools support conversational AutoGen workflows?

They integrate natively. The output from getvendorcategories converts into standard text messages that your agents read and discuss in their shared chat interface.

Manage Foodpanda operations with AutoGen. Let specialized agents debate menu pricing and kitchen capacity before executing updates.

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Connect Foodpanda MCP to AutoGen

Create your Vinkius account to connect Foodpanda to AutoGen 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 AutoGen

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Perplexity

Autonomous menu updates

The Foodpanda MCP Server equips your AutoGen agents with the exact tools needed to manage restaurant inventory. You assign `get_vendor_catalog` and `get_vendor_categories` to an analyst agent that reviews current pricing. A separate manager agent proposes changes, and once they agree, it fires `update_vendor_catalog` to push the new prices live. This multi-agent debate prevents costly typos. If the manager suggests a ninety percent discount, the analyst flags the anomaly before the system touches `upsert_promotion`. They track the resulting deployment by calling `get_promotion_job` and confirm the changes hit the live application.

AutoGen handles rush hour logistics

Kitchens get overwhelmed, and human managers miss the signals. You build a monitoring agent that polls `get_order_history` to measure incoming ticket volume. When the count exceeds a defined threshold, it alerts an operations agent. The operations agent reads the current state via `get_vendor_status`. It then negotiates with the monitoring agent on the best course of action. If they reach consensus that the kitchen is drowning, the operations agent executes `update_vendor_status` to mark the store as busy, temporarily pausing new deliveries.

Resolve tickets with the MCP Server

AutoGen shines when handling complex customer complaints. A support agent receives a refund request and uses `get_order_details` to verify the missing items. It passes this context to a policy agent, which determines if the refund falls within acceptable margins. If the policy agent approves, the support agent calls `update_order` to process the adjustment immediately. You remove the manual review bottleneck. The agents handle the verification, debate the policy application, and execute the final API call.

Setup guide

Set up Foodpanda MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Foodpanda tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Foodpanda_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Foodpanda data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Foodpanda_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Foodpanda data")
    print(result.messages[-1].content)

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 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 AutoGen

Use the autogen-ext[mcp] package. Initialize mcp_server_tools with your Vinkius HTTP transport parameters, and pass the resulting list directly to your AssistantAgent constructor.

Yes. You assign upsert_promotion to a specific agent and require approval from a secondary reviewer agent before the system executes the tool.

The executing agent calls add_catalog_products and receives a job ID. It then loops get_catalog_job until the platform confirms the task finished.

They integrate natively. The output from get_vendor_categories converts into standard text messages that your agents read and discuss in their shared chat interface.

Agents access street addresses and phone numbers through get_order_details. The Vinkius infrastructure processes these requests via stateless functions, ensuring no personal identifiable information ever writes to a persistent disk log.

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