What credentials do I need for NetSuite authentication?

You need 5 values for Token-Based Authentication (TBA): Account ID, Consumer Key, Consumer Secret, Token ID, and Token Secret. All are generated within your NetSuite account under Setup > Integration.

Can I run custom SuiteQL queries?

Yes. The `execute_suiteql` tool executes SQL-like queries against the SuiteQL endpoint. You can query any record type, join tables, and use aggregation functions — all through natural language that the agent translates to SuiteQL.

Does it support NetSuite saved searches?

Absolutely. Use the `run_saved_search` tool with the saved search ID to retrieve its results. This works with any existing saved search in your account — transactions, customers, items, or custom records.

Can I create sales orders through the agent?

Yes. The `create_record` tool with the `salesOrder` record type lets you create full sales orders with line items, pricing, shipping addresses, and payment terms — all through conversation.

Oracle NetSuite MCP Server for Google ADK 9 tools — connect in under 2 minutes

Name: Oracle NetSuite
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 9 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Oracle NetSuite as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="oracle_netsuite_agent",
    instruction=(
        "You help users interact with Oracle NetSuite "
        "using 9 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

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Ed25519Audit chain

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Oracle NetSuite MCP Server

Connect your Oracle NetSuite account to any AI agent and manage your unified ERP operations through natural conversation.

Google ADK natively supports Oracle NetSuite as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 9 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

What you can do

Financial Management — Query G/L account balances, post journal entries, and retrieve trial balance reports across subsidiaries
Sales Orders — Create and manage sales orders, check fulfillment status, and view invoice history
Purchase Orders — Create POs, track receipt status, and manage vendor bill matching
Inventory & Items — Query item records, stock levels by location, and inventory valuations
Customer Records — Create, read, and update customer master data including contacts and credit limits
Saved Searches — Execute NetSuite saved searches to retrieve complex, pre-filtered datasets
SuiteQL Queries — Run advanced SQL-like queries against any NetSuite record type using SuiteQL

The Oracle NetSuite MCP Server exposes 9 tools through the Vinkius. Connect it to Google ADK 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 Oracle NetSuite to Google ADK via MCP

Follow these steps to integrate the Oracle NetSuite MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 9 tools from Oracle NetSuite via MCP

Why Use Google ADK with the Oracle NetSuite MCP Server

Google ADK provides unique advantages when paired with Oracle NetSuite through the Model Context Protocol.

Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Oracle NetSuite

Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

Seamless integration with Google Cloud services means you can combine Oracle NetSuite tools with BigQuery, Vertex AI, and Cloud Functions

Oracle NetSuite + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Oracle NetSuite MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Oracle NetSuite and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Oracle NetSuite tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Oracle NetSuite regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Oracle NetSuite

Oracle NetSuite MCP Tools for Google ADK (9)

These 9 tools become available when you connect Oracle NetSuite to Google ADK via MCP:

create_record

Provide the record type and a JSON body with field values. Example record types: customer, salesOrder, purchaseOrder, journalEntry. Create a new NetSuite record

delete_record

This action is irreversible. Delete a NetSuite record

execute_suiteql

SuiteQL supports SELECT, JOIN, WHERE, GROUP BY, ORDER BY, and aggregate functions. Example: SELECT id, companyname FROM customer WHERE isinactive = 'F' ORDER BY companyname Execute a SuiteQL query

get_record

Common types: customer, vendor, salesOrder, purchaseOrder, invoice, employee, item, inventoryItem. Get a specific NetSuite record

get_record_metadata

Useful for understanding what fields are available before creating or updating records. Get metadata for a NetSuite record type

list_customers

List NetSuite customers

list_records

Common types: customer, vendor, employee, salesOrder, purchaseOrder, invoice, inventoryItem. List NetSuite records by type

list_sales_orders

List recent sales orders

update_record

Only specify the fields you want to change. Update an existing NetSuite record

Example Prompts for Oracle NetSuite in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with Oracle NetSuite immediately.

"Show me the revenue breakdown by subsidiary for March 2026."

"Find all customers with overdue invoices above $10,000."

"Create a sales order for customer 'CUST-1045' with 100 units of item 'SKU-2024-A' at $45 each."

Troubleshooting Oracle NetSuite MCP Server with Google ADK

Common issues when connecting Oracle NetSuite to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Oracle NetSuite + Google ADK FAQ

Common questions about integrating Oracle NetSuite MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.