itemit-mcp
An MCP server for asset tracking that connects to the itemit asset management API.
itemit-mcp
itemit-mcp is an MCP server for asset tracking, providing a bridge between the itemit asset management API and the Model Context Protocol (MCP) ecosystem.
Built and maintained by the uminai MCP team.
Table of Contents
- Overview
- Prerequisites
- Obtaining itemit API Credentials
- Installation & Build
- MCP Client Configuration
- Environment Variables
- Available MCP Tools
- Example Usage
- Response Format
- Credits & Further Resources
Overview
itemit-mcp exposes a set of tools for interacting with the itemit asset management platform via the MCP protocol. It allows you to search, create, and manage assets and locations programmatically, making it easy to integrate itemit with other MCP-enabled systems. Following tools available:
- Get List of items
- Get item by name search
- Create item
- Location Search (With item list on it)
Prerequisites
- Node.js (v16+ recommended)
- Access to an itemit account (to obtain API credentials)
- MCP Client (see uminai MCP for more info)
Obtaining itemit API Credentials
To use this MCP server, you need API credentials from itemit:
ITEMIT_API_KEYITEMIT_USER_IDITEMIT_USER_TOKENITEMIT_WORKSPACE_ID
You can obtain these by signing up or logging in at itemit and following their API documentation or contacting their support.
Installation & Build
Clone this repository and install dependencies:
npm install
Build the project:
npm run build
MCP Client Configuration
Add the following to your MCP Client configuration (e.g., cline_mcp_settings.json):
{
"mcpServers": {
"itemit-mcp": {
"disabled": false,
"timeout": 60,
"type": "stdio",
"command": "node",
"args": [
"/Users/<user>/Documents/itemit-mcp/build/index.js"
],
"env": {
"ITEMIT_API_KEY": "<YOUR_API_KEY>",
"ITEMIT_USER_ID": "<YOUR_USER_ID>",
"ITEMIT_USER_TOKEN": "<YOUR_USER_TOKEN>",
"ITEMIT_WORKSPACE_ID": "<YOUR_WORKSPACE_ID>"
}
}
}
}
Replace the placeholder values with your actual itemit credentials.
Environment Variables
ITEMIT_API_KEY: Your itemit API keyITEMIT_USER_ID: Your itemit user IDITEMIT_USER_TOKEN: Your itemit user tokenITEMIT_WORKSPACE_ID: Your itemit workspace ID
These can be set in your environment or in a .env file.
Available MCP Tools
1. get-location-by-name
- Description: Get locations by name in itemit.
- Parameters:
name(string, required): Name of the location to search forlimit(integer, optional): Number of locations to retrieve (default 25, max 100)skip(integer, optional): Number of locations to skip (default 0)
- Example:
{ "name": "Warehouse" }
2. search-item-by-name
- Description: Search for items by name in itemit.
- Parameters:
name(string, required): Name of the item to search forsize(integer, optional): Number of items to retrieve (default 15, max 100)page(integer, optional): Page number (default 1)
- Example:
{ "name": "Laptop" }
3. create-item
- Description: Create an item in itemit.
- Parameters:
name(string, required): Name of the itemdescription(string, required): Description of the itemserial(string, required): Serial number of the item
- Example:
{ "name": "Projector", "description": "Epson HD Projector", "serial": "SN123456" }
4. get-reminders
- Description: Get reminders from itemit.
- Parameters: None
5. get-items
- Description: Get items from itemit.
- Parameters:
size(integer, optional): Number of items to retrieve (default 15, max 100)
- Example:
{ "size": 10 }
Example Usage
Use your MCP Client to invoke these tools. For example, to search for an item:
{
"tool": "search-item-by-name",
"arguments": {
"name": "Laptop"
}
}
Response Format
All responses are returned as structured text or JSON, matching the itemit API's data model. For example, a successful search might return:
{
"content": [
{
"type": "text",
"text": "Search results for \"Laptop\" (size=15):\n1. Dell XPS 13 (ID: 1234)\n2. MacBook Pro (ID: 5678)\n..."
}
]
}
Credits & Further Resources
- Project by the uminai MCP team.
- Powered by itemit.
- Discover more MCP servers and integrations at mcp.umin.ai.
เซิร์ฟเวอร์ที่เกี่ยวข้อง
Kone.vc
ผู้สนับสนุนMonetize your AI agent with contextual product recommendations
Vercel MCP Server
An MCP server deployed on Vercel that provides a dice rolling tool.
Nexus-mcp-server
Agent-native Ops OS for ecommerce and retail — CRM, orders, inventory, fulfillment, shipping, omnichannel messaging, and AI analytics. All through a single MCP connection.
llmconveyors-mcp
39 tools for the LLM Conveyors AI agent platform. Run Job Hunter, B2B Sales, ATS scoring, resume rendering, and more from any MCP client.
СБОРКА Career
Real-time salary data, job market trends, resume review, interview prep, and career advice for the Russian IT market. Powered by hh.ru API.
Backlog
Integrates with the Backlog API to manage projects and issues.
Avocado AI
Collaborative AI creative workspace for agencies and ecommerce teams to generate on-brand images, videos, and ad creative at scale.
WeRead
Access your WeChat Reading (微信读书) bookshelf, notes, highlights, and reviews.
PPC Ad Editor - Generate Ad Previews Inside AI Agents
Create Google, Meta, and LinkedIn ad previews instantly from Claude, Cursor, or any MCP client—no account or setup required.
Wisembly
Interacts with the Wisembly API to fetch event data.
PDFCheck MCP
View PDF metadata, detect AI-generated content, check edit history & verify authenticity.