How to Use the Duoplane MCP in LlamaIndex

Q: How do I register Duoplane MCP tools with a LlamaIndex agent?

Install llama-index-tools-mcp and initialize the BasicMCPClient with your Duoplane URL. Convert the client tools using McpToolSpec and pass them to your FunctionAgent to start querying vendor data.

Q: Can LlamaIndex index Duoplane purchase orders for semantic search?

Yes, you can use listpurchaseorders to fetch PO records and index them as document nodes in LlamaIndex. This lets your agent answer complex questions about order histories and vendor fulfillment trends.

Q: How does LlamaIndex handle live Duoplane inventory checks?

The agent uses quickvendorinventoryaudit to fetch current stock summaries, which LlamaIndex can temporarily index or query directly. This ensures your RAG pipeline uses live vendor numbers rather than stale cached data.

Index live Duoplane vendor profiles and order statuses directly into LlamaIndex vector stores for semantic retrieval.

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Connect Duoplane MCP to LlamaIndex

Create your Vinkius account to connect Duoplane 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 Duoplane with LlamaIndex

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Index Duoplane order data in LlamaIndex

`list_ecommerce_orders` pulls recent customer transactions directly into your LlamaIndex data ingestion pipeline. The framework indexes these order details as document nodes, making historical purchase data semantically searchable by your agent. When a customer asks about a past purchase, your agent queries this vector index instead of hitting the live database repeatedly. This reduces API load while ensuring the agent retrieves correct order details based on natural language queries.

Search Duoplane vendor profiles semantically

`list_active_vendors` retrieves your complete supplier registry and converts the metadata into queryable vectors. LlamaIndex stores these profiles, allowing your agent to match product sourcing requests with the right vendor capabilities instantly. If you need to find a supplier handling specific shipping terms, the agent searches the vector store rather than manually parsing raw JSON. This combines live Duoplane data with local semantic search to speed up vendor selection.

Query Duoplane inventory audits with LlamaIndex RAG

`quick_vendor_inventory_audit` feeds high-level stock counts into your LlamaIndex knowledge base for real-time analysis. The framework indexes these summaries alongside your storefront catalog documents to highlight sync failures. Your agent queries this combined index to locate products that are active on your storefront but missing from vendor feeds. By checking `list_synced_products`, the agent identifies exact mismatch patterns and lists them in your daily audit report.

Setup guide

Set up Duoplane 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 Duoplane 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 Duoplane tools.",
)
response = await agent.run("List recent Duoplane 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 Duoplane. 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 Duoplane MCP in LlamaIndex

Install `llama-index-tools-mcp` and initialize the `BasicMCPClient` with your Duoplane URL. Convert the client tools using `McpToolSpec` and pass them to your `FunctionAgent` to start querying vendor data.

Yes, you can use `list_purchase_orders` to fetch PO records and index them as document nodes in LlamaIndex. This lets your agent answer complex questions about order histories and vendor fulfillment trends.

The agent uses `quick_vendor_inventory_audit` to fetch current stock summaries, which LlamaIndex can temporarily index or query directly. This ensures your RAG pipeline uses live vendor numbers rather than stale cached data.

Yes, when setting up the MCP Server client in LlamaIndex, you can use the `allowed_tools` filter. This lets you restrict your agent to read-only tools like `get_duoplane_account_metadata` while blocking write operations.

Your Duoplane customer orders and purchase details are processed locally within your LlamaIndex runtime. The Vinkius MCP sandbox isolates the server execution, ensuring your dropship vendor profiles and transaction logs are never exposed or stored externally.

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