EZO Asset Intelligence MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect EZO Asset Intelligence through the Vinkius and every tool is available as a typed function — ready for React Server Components, API routes, or any Node.js backend.
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Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token — get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using EZO Asset Intelligence, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
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.
The Vercel AI SDK gives every EZO Asset Intelligence tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through the Vinkius and stream results progressively to React, Svelte, or Vue components — works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
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 Vercel AI SDK 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 Vercel AI SDK via MCP
Follow these steps to integrate the EZO Asset Intelligence MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 10 tools from EZO Asset Intelligence and passes them to the LLM
Why Use Vercel AI SDK with the EZO Asset Intelligence MCP Server
Vercel AI SDK provides unique advantages when paired with EZO Asset Intelligence through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime — same EZO Asset Intelligence integration everywhere
Built-in streaming UI primitives let you display EZO Asset Intelligence tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
EZO Asset Intelligence + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the EZO Asset Intelligence MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query EZO Asset Intelligence in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate EZO Asset Intelligence tools and return structured JSON responses to any frontend
Chatbots with tool use: embed EZO Asset Intelligence capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with EZO Asset Intelligence through natural language queries
EZO Asset Intelligence MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect EZO Asset Intelligence to Vercel AI SDK 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 Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK 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 Vercel AI SDK
Common issues when connecting EZO Asset Intelligence to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpEZO Asset Intelligence + Vercel AI SDK FAQ
Common questions about integrating EZO Asset Intelligence MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.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 Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.