How to Use the Flexport Logistics MCP in LlamaIndex

Q: How do I connect the Flexport Logistics MCP Server to LlamaIndex?

Install llama-index-tools-mcp and instantiate the BasicMCPClient with your Vinkius endpoint. Convert it using McpToolSpec and call totoollistasync() to pass the tools directly to your LlamaIndex agent.

Q: Can I index my return history using Flexport Logistics and LlamaIndex?

Yes, your agent can call listreturns to fetch return records and getreturn for specific item details, then index these documents into your LlamaIndex vector store for semantic analysis.

Q: Can my agent search across multiple warehouses using this setup?

Yes. LlamaIndex queries the warehouse map using getwarehousenetwork and indexes the location data so your agent can instantly match the nearest facility to a customer's address.

Q: How is my logistics data protected during LlamaIndex vector searches?

Your sensitive order details from getlogisticsorder are processed locally inside your LlamaIndex application. The MCP Server communicates through a secure, single-token Vinkius sandbox to keep your supply chain data isolated.

Index live Flexport Logistics data into LlamaIndex vector stores to query your actual inventory in real time.

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Connect Flexport Logistics MCP to LlamaIndex

Create your Vinkius account to connect Flexport Logistics to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Flexport Logistics with LlamaIndex

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Build RAG Pipelines Grounded in Real Warehouse Data

Stop guessing your stock levels or relying on stale spreadsheet exports. This MCP server lets your LlamaIndex agent fetch actual numbers using `list_inventory` and feed them directly into your vector index, grounding your customer support bot in real-time truth. When a customer asks if an item is in stock, the agent queries the live catalog using `list_products` and cross-references it with warehouse data. The response is generated using actual operational data, eliminating the risk of selling items you do not have.

Search Your Inbounds and Returns Semantically

LlamaIndex can index complex shipping payloads so you can query them using natural language. Your agent pulls recent inbound shipments via `list_inbounds` and details via `get_inbound`, creating a searchable knowledge base of your incoming inventory. You can ask questions like "Are there any delayed shipments?" and the LlamaIndex agent will parse the data retrieved from `get_warehouse_network` to find the answer. It turns raw JSON responses into a searchable memory.

Automate E-Commerce Fulfillment via LlamaIndex Agents

This integration lets your agent take direct action based on semantic queries. If a query reveals that a VIP order is missing, the LlamaIndex agent can immediately invoke `create_logistics_order` to trigger a replacement shipment. The agent verifies the product details via `get_product` and pulls the required shipping labels using `list_labels` to complete the transaction. You get a closed-loop system where data indexing leads directly to operational action.

Setup guide

Set up Flexport Logistics MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Flexport Logistics MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Flexport Logistics tools.",
)
response = await agent.run("List recent Flexport Logistics data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Flexport Logistics. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Flexport Logistics MCP in LlamaIndex

Install `llama-index-tools-mcp` and instantiate the `BasicMCPClient` with your Vinkius endpoint. Convert it using `McpToolSpec` and call `to_tool_list_async()` to pass the tools directly to your LlamaIndex agent.

Yes, your agent can call `list_returns` to fetch return records and `get_return` for specific item details, then index these documents into your LlamaIndex vector store for semantic analysis.

By using this MCP Server, LlamaIndex bypasses static training data and queries live inventory via `list_inventory` before generating answers, ensuring all stock levels are accurate.

Yes. LlamaIndex queries the warehouse map using `get_warehouse_network` and indexes the location data so your agent can instantly match the nearest facility to a customer's address.

Your sensitive order details from `get_logistics_order` are processed locally inside your LlamaIndex application. The MCP Server communicates through a secure, single-token Vinkius sandbox to keep your supply chain data isolated.

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