EZO Asset Intelligence MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add EZO Asset Intelligence as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to EZO Asset Intelligence. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in EZO Asset Intelligence?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About EZO Asset Intelligence MCP Server
Integrate EZO.io (formerly EZOfficeInventory), the world's most popular asset management platform, directly into your AI workflow. Manage your fixed asset database and physical locations, track consumable inventory and real-time stock levels, monitor active checkouts and reservations, and oversee your entire asset lifecycle using natural language.
LlamaIndex agents combine EZO Asset Intelligence tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Asset Oversight — List and retrieve detailed information, identifiers, and maintenance history for all your managed assets.
- Inventory Intelligence — Monitor consumable inventory items, resolving available quantities and stock thresholds across your organization.
- Checkout Management — Access and monitor currently checked out assets, identifying assigned members and expected return dates.
- Asset Auditing — Retrieve high-level summaries of asset volume, location distribution, and organizational resource health instantly.
The EZO Asset Intelligence MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect EZO Asset Intelligence to LlamaIndex via MCP
Follow these steps to integrate the EZO Asset Intelligence MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from EZO Asset Intelligence
Why Use LlamaIndex with the EZO Asset Intelligence MCP Server
LlamaIndex provides unique advantages when paired with EZO Asset Intelligence through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine EZO Asset Intelligence tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain EZO Asset Intelligence tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query EZO Asset Intelligence, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what EZO Asset Intelligence tools were called, what data was returned, and how it influenced the final answer
EZO Asset Intelligence + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the EZO Asset Intelligence MCP Server delivers measurable value.
Hybrid search: combine EZO Asset Intelligence real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query EZO Asset Intelligence to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying EZO Asset Intelligence for fresh data
Analytical workflows: chain EZO Asset Intelligence queries with LlamaIndex's data connectors to build multi-source analytical reports
EZO Asset Intelligence MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect EZO Asset Intelligence to LlamaIndex via MCP:
get_asset_detailed_data
Get detailed settings and information for a specific asset
get_ezo_account_metadata
Retrieve metadata and limits for your EZO account
list_account_members
List all members and users registered in your organization
list_asset_locations
List all physical locations and sub-locations configured in your account
list_available_assets
Identify assets that are currently available for checkout
list_consumable_inventory
List all consumable inventory items and their stock levels
list_currently_checked_out_assets
Identify all assets that are currently checked out to members
list_managed_assets
g. available, checked out) from the EZO API. List all fixed assets managed in your EZO account
list_overdue_checkouts
Identify assets that are past their expected return date (mock logic)
quick_asset_volume_audit
Retrieve a high-level summary of assets, inventory, and members
Example Prompts for EZO Asset Intelligence in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with EZO Asset Intelligence immediately.
"List all assets currently checked out."
"Show me our inventory levels for 'Ethernet Cables'."
"Check for overdue asset returns."
Troubleshooting EZO Asset Intelligence MCP Server with LlamaIndex
Common issues when connecting EZO Asset Intelligence to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpEZO Asset Intelligence + LlamaIndex FAQ
Common questions about integrating EZO Asset Intelligence MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect EZO Asset Intelligence with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect EZO Asset Intelligence to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.