How to Use the ShipStation MCP in LlamaIndex
Index ShipStation API results and query your shipping history with LlamaIndex.
Works with every AI agent you already use
…and any MCP-compatible client
Connect ShipStation MCP to LlamaIndex
Create your Vinkius account to connect ShipStation to LlamaIndex — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.
Key Capabilities
Building a Searchable Shipping Knowledge Base
LlamaIndex lets you index the output of `get_rates` into a vector store. Instead of just getting rates, you build a knowledge base where users can query things like: 'What was our cheapest shipping option for an item weighing 5 lbs in California?' This capability means your agent doesn't hallucinate; it grounds answers in the actual data retrieved from `get_rates` and other rate-related calls.
Retrieving Historical Order Data Context
Want to know how a specific customer handled their last shipment? Use LlamaIndex to index records from `list_orders`. You can then query the knowledge base using the customer's name or ID, getting detailed answers grounded in past order data. This is powerful for troubleshooting. Your agent retrieves contextual information—like old tags applied or previous warehouse locations (`list_warehouses`)—to inform current decisions.
Tracking Account and Fulfillment Changes
LlamaIndex indexes account-level changes. You can feed the results from `add_funds` or `update_store` into your index. This allows you to build a historical record of operational settings, answering questions like: 'When did we last update the billing address for Store X?' This makes compliance and auditing easier because every change is searchable API data.
Set up ShipStation MCP in LlamaIndex
Prerequisites
- Python 3.10+ installed
-
llama-index-tools-mcppackage - 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 providesBasicMCPClientandMcpToolSpec. - 2
Connect with BasicMCPClient
Point
BasicMCPClientto 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 ShipStation MCP tools into nativeFunctionToolobjects that any LlamaIndex agent can use. - 4
Run with any LLM
Create a
FunctionAgentwith the tools and your preferred LLM. SwapOpenAIforAnthropic,Gemini, or any LlamaIndex-supported provider.
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 ShipStation tools.",
)
response = await agent.run("List recent ShipStation data") Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ShipStation. 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.
Why Choose Vinkius
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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
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Common questions about ShipStation MCP in LlamaIndex
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