How to Use the EZO Asset Intelligence MCP in LlamaIndex

Index your inventory data into LlamaIndex to build RAG applications that answer questions about your assets with precision.

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Connect EZO Asset Intelligence MCP to LlamaIndex

Create your Vinkius account to connect EZO Asset Intelligence 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 EZO Asset Intelligence with LlamaIndex

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Index inventory for LlamaIndex RAG

Convert live asset records into searchable vector embeddings. Your agent uses `list_managed_assets` to fetch data, which then populates your knowledge base for semantic retrieval. This turns your inventory into a queryable source of truth. Instead of guessing asset status, your agent searches the index to provide grounded answers based on the latest API results.

Query asset history with MCP Server tools

Retrieve deep insights by combining historical logs with your indexed documents. Use `get_asset_detailed_data` to feed specific asset histories into your context window. This approach allows for complex queries about equipment life cycles. You avoid hallucinations by forcing the agent to reference the specific data returned by the tool.

Track consumables using MCP Server data

Monitor stock levels of your non-fixed equipment within your knowledge graph. The agent calls `list_consumable_inventory` to ensure your index reflects current availability. This keeps your RAG application aware of real-time supply changes. It prevents the agent from recommending assets that are already out of stock.

Setup guide

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

You use the MCP tool spec to convert API functions into a list of tools for your agent. This makes your live EZO data available for semantic indexing.

Yes. By indexing the output of the tool calls, you create a searchable knowledge base that combines EZO asset details with your existing documentation.

The server fetches data directly from the API at runtime. Your LlamaIndex application always queries the current state of your assets.

You provide an endpoint token that handles authentication. The server never logs or caches your sensitive API keys.

Data privacy is strictly maintained. The server only transmits asset metadata to your local agent environment, ensuring no third party sees your inventory records.

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