MCP Sample Tools
As of September 2025, the MCP Sample Tools SuiteApp is no longer available for new installations. It has been replaced by the MCP Standard Tools SuiteApp, which is available for installation from the SuiteApp Marketplace. For more information, see MCP Standard Tools SuiteApp.
If the MCP Sample Tools SuiteApp is still installed in your account, you should uninstall it and switch to the MCP Standard Tools SuiteApp as soon as possible. There will be no further updates or fixes for existing installations of the MCP Sample Tools SuiteApp. Additionally, the SuiteApp will stop working at any time from December 2025 onward. For information about uninstalling SuiteApps, see Uninstalling SuiteApps Obtained from the SuiteApp Marketplace.
The sample tools remain available in the MCP-Sample-Tools directory of the SuiteCloud Project Repository on Oracle Samples GitHub, for reference or as a starting point for building your own custom tools.
The MCP Sample Tools are designed for use with the NetSuite AI Connector Service and provide basic examples of how to perform NetSuite operations using conversational AI. These tools let you interact with NetSuite using natural language commands from an AI client that communicates through Model Context Protocol (MCP). The MCP Sample Tools serve as a starting point for building your own solutions, demonstrating how SuiteScript and the SuiteCloud Development Framework (SDF) can be used to enable natural language interactions with NetSuite.
These tools are designed to work with your existing NetSuite roles and permissions. It uses the same access controls as the NetSuite UI, so you can only see data and take actions allowed by your assigned roles.
To learn more about the sample tools, see Available Tools in the MCP Sample Tools.
NetSuite also provides the MCP Standard Tools SuiteApp, which you can install from the SuiteApp Marketplace. This SuiteApp includes tools for running custom SuiteQL queries, accessing NetSuite reports and saved searches, and creating or updating records using REST Web Services. For more information, see MCP Standard Tools SuiteApp.
Key Features
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Conversational Data Access – Retrieve information about NetSuite records (such as customers, transactions, and financial data) using natural language queries.
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Record Operations – Create or update records through conversational commands. Supported operations are securely executed according to your NetSuite permissions.
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Data Visualization – View information in user-friendly formats such as tables and summaries that are compatible with the AI client's display capabilities.
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Permission Compliance – All data access and actions are determined by your NetSuite role and permissions. The tools don't provide any additional access beyond what your NetSuite role allows. Your ability to view data, perform operations, or use specific tools depends on the permissions assigned to the NetSuite role you use to connect.
How MCP Sample Tools Work
The MCP Sample Tools enable you to interact with NetSuite data using conversational AI. The typical workflow includes the following steps:
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Download MCP Sample Tools
Download MCP-Sample-Tools from the SuiteCloud Project Repository on Oracle Samples GitHub and deploy the project to your NetSuite account.
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Invoke Tools through Conversational AI
After deploying the project, connect to the AI client to start using the tools. See Connect to NetSuite AI Connector Service.
Open the AI client and start a conversation using natural language commands or queries. The conversational AI interprets your request and presents you with a set of available tools and actions. The tools you see in the AI client depend on the permissions defined for each tool. A tool is visible only if your role has all the required permissions for that tool. For more information about the available tools, see Available Tools in the MCP Sample Tools.
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Perform Operations
When you make a request through the AI client, your commands are translated into the appropriate NetSuite API calls or operations.
The tools perform the task in NetSuite, such as retrieving records or updating information. The results are then returned to the AI client, where you can view the outcome directly in your conversation interface.