CartonCloud MCP Server for LlamaIndex 8 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add CartonCloud as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to CartonCloud. "
"You have 8 tools available."
),
)
response = await agent.run(
"What tools are available in CartonCloud?"
)
print(response)
asyncio.run(main())
* 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.
LlamaIndex agents combine CartonCloud tool responses with indexed documents for comprehensive, grounded answers. Connect 8 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the CartonCloud MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
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
Why Use LlamaIndex with the CartonCloud MCP Server
LlamaIndex provides unique advantages when paired with CartonCloud through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine CartonCloud tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain CartonCloud tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query CartonCloud, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what CartonCloud tools were called, what data was returned, and how it influenced the final answer
CartonCloud + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the CartonCloud MCP Server delivers measurable value.
Hybrid search: combine CartonCloud real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query CartonCloud to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying CartonCloud for fresh data
Analytical workflows: chain CartonCloud queries with LlamaIndex's data connectors to build multi-source analytical reports
CartonCloud MCP Tools for LlamaIndex (8)
These 8 tools become available when you connect CartonCloud to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting CartonCloud to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpCartonCloud + LlamaIndex FAQ
Common questions about integrating CartonCloud MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect CartonCloud with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect CartonCloud to LlamaIndex
Get your token, paste the configuration, and start using 8 tools in under 2 minutes. No API key management needed.