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 CrewAI 10 tools — connect in under 2 minutes

Name: Kargo
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Kargo through the Vinkius — pass the Edge URL in the `mcps` parameter and every Kargo tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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

from crewai import Agent, Task, Crew

agent = Agent(
    role="Kargo Specialist",
    goal="Help users interact with Kargo effectively",
    backstory=(
        "You are an expert at leveraging Kargo tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Kargo "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

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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.

When paired with CrewAI, Kargo becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Kargo tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the Kargo MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 10 tools from Kargo

Why Use CrewAI with the Kargo MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Kargo through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Kargo + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Kargo for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Kargo, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Kargo tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Kargo against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Kargo MCP Tools for CrewAI (10)

These 10 tools become available when you connect Kargo to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Kargo + CrewAI FAQ

Common questions about integrating Kargo MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.