How to Use the Veeqo MCP in LlamaIndex

Q: Can I use LlamaIndex to query past Veeqo order records?

Yes. You index the results of getorderdetails. This means you can ask natural language questions about specific orders, and your agent pulls the answer from the indexed data.

Q: How can I get current inventory status using LlamaIndex and Veeqo?

You run listinventoryproducts to get the live data, then index it. You can then query that knowledge base to check stock levels without needing a live API call every time.

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Connect Veeqo MCP to LlamaIndex

Create your Vinkius account to connect Veeqo 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 Veeqo with LlamaIndex

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Search Historical Order Data

You can index the output of `list_orders` and `get_order_details`. Instead of manually listing orders, you query your index to ask questions like, 'What were the typical shipping costs for electronics in Q3?' The resulting answers are grounded in actual Veeqo API data, eliminating hallucinations.

Product Knowledge Indexing

Run `list_inventory_products` and index the results. Later, you can ask your agent about product compatibility or stock levels without calling the live tool again. The indexed data becomes part of a unified knowledge base for semantic search.

Customer Profile Retrieval

LlamaIndex lets you index customer lists generated by `list_customers`. You can then query this historical record to understand patterns—for example, finding all customers who bought a specific item over the last year. The results combine live API data with your own documents for comprehensive insights.

Setup guide

Set up Veeqo 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 Veeqo 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 Veeqo tools.",
)
response = await agent.run("List recent Veeqo data")

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Common questions about Veeqo MCP in LlamaIndex

LlamaIndex indexes the output from MCP tools. When you run a tool like `list_shipments`, that structured data is written to a vector store, making it searchable context for future queries.

Yes. You index the results of `get_order_details`. This means you can ask natural language questions about specific orders, and your agent pulls the answer from the indexed data.

It does. By combining live tool outputs with static documents (like internal pricing guides), you build RAG applications that provide answers grounded in both your knowledge and the Veeqo data.

The server touches customer records, specifically detailed order information from `get_order_details`. Always ensure your vector store security matches your compliance needs.

You run `list_inventory_products` to get the live data, then index it. You can then query that knowledge base to check stock levels without needing a live API call every time.

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