How to Use the Uber Eats MCP in CrewAI

Q: How does Uber Eats integration work with CrewAI?

You assign roles: one agent researches the store via getstore, another analyzes the menu using getmenus, and a third acts by calling tools like acceptorder. This specialization makes complex operations possible.

Q: Can CrewAI handle Uber Eats data privacy?

Absolutely. You can create an 'Audit Agent' that uses getorderissues. This pulls all complaint details, issue descriptions, and refund statuses into a shared memory for review.

Q: Do I need to know store IDs for Uber Eats with CrewAI?

Yes. The initial step must be running getstores so the crew can acquire all necessary external store IDs and operational details before any other tool call is made.

Q: If I encounter issues with Uber Eats using CrewAI, where do I check?

The 'Resolution Agent' uses getorderissues to systematically pull all complaint records. This process gives the team a complete history of disputes and resolution efforts.

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Connect Uber Eats MCP to CrewAI

Create your Vinkius account to connect Uber Eats to CrewAI 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 Uber Eats with CrewAI

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Autonomous Order Fulfillment via MCP Server

Set up a dedicated 'Fulfillment Agent.' This agent first uses `get_orders` to pull pending IDs. A second 'Prep Agent' then takes that ID and calls `accept_order`. The system runs the full process without human intervention. This sequential, collaborative approach ensures that order management moves from PENDING to ACCEPTED reliably.

Menu and Inventory Management with CrewAI

A dedicated 'Inventory Agent' manages stock. It runs `get_menus` to review the entire catalog, then uses `update_menu_item_availability` when ingredients run low. This agent reports back which items need immediate attention. It ensures that your restaurant only lists what it actually has in stock before a customer places an order.

Dispatch Coordination with MCP Server

Need to tell the courier the food is ready? The 'Dispatcher Agent' watches for accepted orders and, when they are complete, calls `mark_order_ready`. This triggers the notification flow. If the order needs to be delayed or cancelled due to a kitchen emergency, this agent uses `cancel_order` with required reasoning.

Setup guide

Set up Uber Eats MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Uber Eats tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Uber Eats Analyst",
    goal="Access and analyze Uber Eats data via MCP.",
    backstory="Expert analyst with direct Uber Eats access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Uber Eats transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

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

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

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

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Uber Eats Analyst",
        goal="Access and analyze Uber Eats data via MCP.",
        backstory="Expert analyst with direct Uber Eats access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Uber Eats transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

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

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 Uber Eats. 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 Uber Eats MCP in CrewAI

You assign roles: one agent researches the store via `get_store`, another analyzes the menu using `get_menus`, and a third acts by calling tools like `accept_order`. This specialization makes complex operations possible.

Your agents run autonomously. For example, one agent monitors all open orders using `get_orders`, and if a status changes to READY, another agent automatically calls `mark_order_ready` to start the courier dispatch.

Absolutely. You can create an 'Audit Agent' that uses `get_order_issues`. This pulls all complaint details, issue descriptions, and refund statuses into a shared memory for review.

Yes. The initial step must be running `get_stores` so the crew can acquire all necessary external store IDs and operational details before any other tool call is made.

The 'Resolution Agent' uses `get_order_issues` to systematically pull all complaint records. This process gives the team a complete history of disputes and resolution efforts.

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