Can I check stock levels for a specific SKU?

Yes! Use the `get_product_stock` tool with the product's unique ID. The agent will return the current available quantities across your warehouses.

How do I see all pending sale orders?

Use the `list_sale_orders` tool. Your agent will fetch the list of outbound orders along with their current status and customer information.

Which regions does this integration support?

It supports all CartonCloud regions. You just need to specify your region subdomain (e.g., `api-au` for Australia, `api-us` for United States) during setup.

CartonCloud MCP Server for Pydantic AI 8 tools — connect in under 2 minutes

Name: CartonCloud
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 8 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect CartonCloud through 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

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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 CartonCloud "
            "(8 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in CartonCloud?"
    )
    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 CartonCloud MCP Server

Connect your CartonCloud account to any AI agent and orchestrate your WMS (Warehouse Management System) and TMS (Transport Management System) through natural conversation. Streamline 3PL operations and inventory management.

Pydantic AI validates every CartonCloud tool response against typed schemas, catching data inconsistencies at build time. Connect 8 tools through 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.

What you can do

Order Fulfillment — List and retrieve details for outbound sale orders and inbound purchase orders natively
Inventory Visibility — Monitor current stock levels by product and warehouse location in real-time
Transport Management — List transport consignments and track delivery statuses securely
Master Data Control — Access warehouse product details, including SKUs and unit of measure metadata
Customer Oversight — List and manage customer profiles and associated logistics data flawlessly
Financial Auditing — Retrieve generated invoices for logistics services directly within your workspace

The CartonCloud MCP Server exposes 8 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 CartonCloud to Pydantic AI via MCP

Follow these steps to integrate the CartonCloud 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 8 tools from CartonCloud with type-safe schemas

Why Use Pydantic AI with the CartonCloud MCP Server

Pydantic AI provides unique advantages when paired with CartonCloud 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 CartonCloud integration code

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

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

CartonCloud + Pydantic AI Use Cases

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

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

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

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

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

CartonCloud MCP Tools for Pydantic AI (8)

These 8 tools become available when you connect CartonCloud to Pydantic AI via MCP:

get_product_stock

Get current stock levels for a specific product

get_sale_order_details

Get details for a specific sale order

list_consignments

List transport consignments

list_logistics_customers

List customers associated with the tenant

list_logistics_invoices

List generated invoices for logistics services

list_purchase_orders

List inbound purchase orders

list_sale_orders

List outbound sale orders

list_warehouse_products

List warehouse products and master data

Example Prompts for CartonCloud in Pydantic AI

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

"List my last 10 sale orders in CartonCloud."

"What is the current stock for product ID 555?"

"Show me the transport consignments for today."

Troubleshooting CartonCloud MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

CartonCloud + Pydantic AI FAQ

Common questions about integrating CartonCloud 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 CartonCloud MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.