Where do I find my Business and Facility Slugs?

These unique identifiers are assigned to your organization by Kargo. You can find them in your dashboard settings or by contacting your Kargo account manager.

Can I check the status of physical devices in the warehouse?

Yes! Use the `list_devices` tool to see all IoT equipment at your facility, and `get_device_status` for detailed health metrics and last-seen timestamps for a specific unit.

What is the Unified Endpoint used for?

The Unified Endpoint allows you to push external order or shipment data into the Kargo system for automated processing and real-time visibility updates.

Kargo MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Kargo
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

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

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 Kargo "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

Fully ManagedVinkius Servers

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DLPData protection

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Ed25519Audit chain

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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 Kargo MCP Server

Connect your Kargo logistics account to your AI agent and optimize your supply chain and loading dock operations through natural conversation.

Pydantic AI validates every Kargo tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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

Shipment Tracking — List all shipments for your facility and get real-time status updates and carrier info.
Order Management — Access facility-wide customer orders and their current status.
Deep Inspection — Fetch complete metadata for specific shipments or orders using their unique numbers.
Data Synchronization — Push order and shipment payload data directly to Kargo's Unified Endpoint to keep systems in sync.
Facility & Device Oversight — List all business facilities and monitor the status of active IoT devices (cameras, sensors).
Audit Logs — Review the history of data payloads pushed to the platform.

The Kargo MCP Server exposes 10 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 Kargo to Pydantic AI via MCP

Follow these steps to integrate the Kargo 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 10 tools from Kargo with type-safe schemas

Why Use Pydantic AI with the Kargo MCP Server

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

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

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

Kargo + Pydantic AI Use Cases

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

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

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

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

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

Kargo MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Kargo to Pydantic AI via MCP:

get_carrier_info

Get carrier contact info

get_device_status

Get specific device status

get_order

Get specific order details

get_shipment

Get specific shipment details

list_devices

List facility IoT devices

list_facilities

List all business facilities

list_orders

List facility orders

list_payload_logs

List sync payload logs

list_shipments

List all shipments at the facility

update_logistics

Sync data to Kargo Unified Endpoint

Example Prompts for Kargo in Pydantic AI

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

"List all active shipments for my facility."

"Check the status of all IoT devices in the facility."

"Get details for shipment number SHP-2024-05."

Troubleshooting Kargo MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Kargo + Pydantic AI FAQ

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