Does this work for iFood customers or only merchants?

This MCP server is designed exclusively for iFood merchants (restaurant owners). It uses the Merchant API to manage orders, catalogs, and operations. Consumer-side features require a different API. If you're a restaurant owner using iFood for delivery, this is for you.

Can I accept and prepare orders automatically with this MCP?

Yes! AI agents can update order status through the full workflow: PENDING -> ACCEPTED -> PREPARING -> READY -> DISPATCHED -> DELIVERED. You can build automation rules to accept orders instantly, notify kitchen staff, and track preparation times.

Does this support multiple restaurant locations?

Absolutely. The API returns all stores associated with your merchant account. Each tool requires a store_id parameter, so you can manage operations independently across all your restaurant locations. AI agents can list all your stores first to get their IDs.

iFood MCP Server for Pydantic AI 11 tools — connect in under 2 minutes

Name: iFood
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 11 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect iFood through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

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

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to iFood "
            "(11 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in iFood?"
    )
    print(result.data)

asyncio.run(main())

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* 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 iFood MCP Server

What you can do

Transform your iFood merchant operations with AI-powered automation. Your agents can:

Pydantic AI validates every iFood tool response against typed schemas, catching data inconsistencies at build time. Connect 11 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.

Monitor incoming orders in real-time with status tracking
Accept and progress orders through preparation workflow
Manage restaurant catalogs — update prices, availability, descriptions
Review order details including customer info, items, and totals
Configure operating hours for each day of the week
Track delivery logistics and assign drivers to orders
View store information and configuration across all locations

The iFood MCP Server exposes 11 tools through the Vinkius. Connect it to Pydantic AI 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 iFood to Pydantic AI via MCP

Follow these steps to integrate the iFood MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 11 tools from iFood with type-safe schemas

Why Use Pydantic AI with the iFood MCP Server

Pydantic AI provides unique advantages when paired with iFood through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your iFood integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your iFood connection logic from agent behavior for testable, maintainable code

iFood + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the iFood MCP Server delivers measurable value.

Type-safe data pipelines: query iFood with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple iFood tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query iFood and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock iFood responses and write comprehensive agent tests

iFood MCP Tools for Pydantic AI (11)

These 11 tools become available when you connect iFood to Pydantic AI via MCP:

assign_driver

Requires order ID and driver ID. Use this to manage your own delivery fleet and coordinate order fulfillment. Assign a delivery driver to an iFood order

get_business_hours

Use this to review or verify the current schedule before making changes. Get operating hours for an iFood store

get_catalog

Use this to review menu structure, check item availability, or prepare updates to pricing or descriptions. Get the menu catalog for an iFood store

get_logistics

Use this to track order fulfillment and coordinate with delivery personnel. Get logistics/delivery information for an iFood order

get_order_details

Use this to review order contents before accepting or preparing. Get complete details of a specific iFood order

get_orders

Can filter by status: PENDING, ACCEPTED, PREPARING, READY, DISPATCHED, DELIVERED, CANCELLED. Returns order number, customer info, items, totals, and timestamps. Use this to monitor order flow and track pending orders. List orders for an iFood store

get_store_details

Use this to review store configuration before making updates. Get detailed information about a specific iFood store

get_stores

Returns store IDs, names, addresses, and operational status. Use this first to get store IDs needed for other operations like fetching orders or managing catalogs. List all stores associated with the iFood merchant account

update_business_hours

Requires a schedule object with open/close times for each day. Use this to change store hours, add weekend schedules, or set holiday closures. The schedule should be a JSON object with day keys (monday, tuesday, etc.) and arrays of {start: "HH:MM", end: "HH:MM"} objects. Update operating hours for an iFood store

update_catalog_item

Only pass the fields you want to change. Common use: update prices, toggle availability, or change descriptions. Requires store ID and item ID. Update a menu item in the iFood store catalog

update_order_status

Common workflow: PENDING -> ACCEPTED -> PREPARING -> READY -> DISPATCHED -> DELIVERED. Can also set to CANCELLED if needed. Use this to progress orders through the fulfillment pipeline. Update the status of an iFood order

Example Prompts for iFood in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with iFood immediately.

"Show me all pending orders and accept them automatically"

"Update the price of 'Combo Burger Especial' to R$32.90 and mark it as unavailable until tomorrow"

"Change my store hours to open at 11am and close at 11pm every day this week"

Troubleshooting iFood MCP Server with Pydantic AI

Common issues when connecting iFood to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

iFood + Pydantic AI FAQ

Common questions about integrating iFood MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your iFood MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.