Integrate LibreChat with Live NetSuite SuiteAnalytics Data via CData Connect AI

Yazhini G
Yazhini G
Technical Marketing Engineer
Leverage the CData Connect AI Remote MCP Server to enable LibreChat to securely access and query live NetSuite SuiteAnalytics data from within the chat interface.

LibreChat is an open-source, self-hosted AI chat platform that brings together multiple LLM providers, agents, and assistants behind a single interface. It also supports the Model Context Protocol (MCP), so you can connect external tools and data sources directly to the chat and pull in live data from the systems you already work with.

By integrating LibreChat with CData Connect AI through the built-in MCP Server, LibreChat gains governed, real-time access to live NetSuite SuiteAnalytics data. This enables you to list catalogs, explore schemas, and query records from NetSuite SuiteAnalytics data using natural language prompts, with all data access running securely against authorized sources.

This article explains how to configure NetSuite SuiteAnalytics connectivity in Connect AI, generate the required personal access token, install LibreChat, register the Connect AI MCP Server, configure an LLM provider, and verify the integration by querying live NetSuite SuiteAnalytics data from the LibreChat interface.

Step 1: Configure NetSuite SuiteAnalytics connectivity for LibreChat

Connectivity to NetSuite SuiteAnalytics from LibreChat is made possible through Connect AI's Remote MCP Server. To interact with NetSuite SuiteAnalytics data from LibreChat, start by creating and configuring a NetSuite SuiteAnalytics connection in Connect AI.

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Adding a connection in Connect AI
  3. Select NetSuite SuiteAnalytics from the Add Connection panel
  4. Selecting data source
  5. Enter the necessary authentication properties to connect to NetSuite SuiteAnalytics.

    Prerequisites

    Before you can connect to NetSuite SuiteAnalytics, you must set up SuiteAnalytics Connect in your NetSuite account:

    1. Enable the Connect Service feature.

      1. Ensure that your Account Administrator has enabled your Account and Role with the Connect Service feature.

      2. Navigate to Setup > Company > Enable Features.

      3. Click the Analytics tab and check the SuiteAnalytics Connect box.

    2. Add the SuiteAnalytics Connect permission to an existing Role, and note the Role ID for later.

    3. Find the Settings portlet on your home page and click Set Up SuiteAnalytics Connect, then click Your Configuration to view your service host and account ID. These settings map directly to the Server and Account Id properties.

    Add the NetSuite SuiteAnalytics Connection

    1. Open the Sources page of the Connect Cloud dashboard.

    2. Click Add Connection and select NetSuite SuiteAnalytics from the list of connectors.

    3. Enter a Connection Name of your choice.

    Authenticate to NetSuite SuiteAnalytics

    Set the following required properties:

    • Server: The Service Host value you found when setting up SuiteAnalytics Connect.

    • Account Id: The Account ID value you found when setting up SuiteAnalytics Connect.

    • Role Id: The internal ID of the login role you granted the SuiteAnalytics Connect permission.

    Next, choose one of the supported authentication methods:

    Basic authentication

    • User: The username you use to authenticate to your NetSuite account.

    • Password: The password associated with that account.

    Token-based authentication

    • Consumer Key and Consumer Secret: Generated when you create your integration record in NetSuite.

    • Token Key and Token Secret: The access token and secret generated for that integration.

    After you enter your credentials, click Save & Test to validate the connection.

    Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab and update user-based permissions
  8. Updating permissions

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from LibreChat. It is best practice to create a separate PAT for each integration to maintain granular access control.

  1. Click the gear icon () at the top right of the Connect AI app to open Settings
  2. On the Settings page, go to the Access Tokens section and click Create PAT
  3. Give the PAT a descriptive name and click Create
  4. Creating a new PAT
  5. Copy the token when displayed and store it securely. It will not be shown again

With the NetSuite SuiteAnalytics connection configured and a PAT generated, LibreChat can now connect to NetSuite SuiteAnalytics data through Connect AI.

Step 2: Install LibreChat and configure Connect AI MCP

Next, install LibreChat locally and configure the Connect AI Remote MCP Server so that the chat interface can discover and call live data tools through Connect AI.

  1. Install LibreChat by following the official installation guide. If you are using the npm setup, make sure MongoDB and MeiliSearch are installed and running locally
  2. Once the installation is complete, start LibreChat and open http://localhost:3080/ in your browser to access the chat interface LibreChat chat interface
  3. In the left navigation bar, click the MCP Settings icon, then click Add MCP Adding a new MCP server in LibreChat
  4. In the Add MCP panel, configure the server with the following values:
    • Name: CData MCP, or any name of your choice
    • Description: Optional description for the server
    • MCP Server URL: https://mcp.cloud.cdata.com/mcp
    • Transport: Streamable HTTPS
    • Authentication: API Key
    • Header Format: Basic
    • API Key: base64-encoded value of email:PAT

    Note: LibreChat will use Basic authentication with Connect AI. Combine your Connect AI user email and the PAT you created earlier in the format email:PAT, then base64 encode the combined string and paste it in the API Key field. For example, [email protected]:ABC123...XYZ789 base64-encoded becomes something like: dXNlckBkb21haW4uY29tOkFCQzEyMy4uLlhZWjc4OQ==

    Configuring the Connect AI MCP Server
  5. Check I trust this application and click Add to save the server
  6. The CData MCP server now appears in the left navigation bar. Click the connect icon next to it to establish the connection to Connect AI CData MCP server connected in LibreChat

Enable the MCP server and configure an LLM provider

LibreChat requires at least one LLM provider to power the chat. Enable the MCP server in the chat input and add an API key for your preferred provider so the model can interpret prompts and call MCP tools through Connect AI.

  1. In the chat interface, click the MCP selector at the bottom of the input box and confirm that CData MCP is checked so the tools are exposed to the chat Enabling the CData MCP server in the chat input
  2. At the top of the chat, click the model selector and choose your preferred LLM provider (e.g., OpenAI, Anthropic, Google) and model Selecting an LLM provider and model
  3. Click Set API Key next to the chosen provider, paste your provider API key, and click Submit Setting the LLM provider API key

With the MCP server and an LLM provider configured, LibreChat is ready to query live NetSuite SuiteAnalytics data through Connect AI.

Step 3: Query live NetSuite SuiteAnalytics data from LibreChat

With the integration complete, use the LibreChat chat input to interact with live NetSuite SuiteAnalytics data through natural language prompts handled by the configured LLM.

  1. With the CData MCP server enabled and a model selected, type a prompt in the chat input, for example:
    • List all catalogs in my cdata mcp
    • Show the available schemas and tables for NetSuite SuiteAnalytics
    • Query the top 5 records from a table in NetSuite SuiteAnalytics data
  2. LibreChat calls the Connect AI MCP Server and returns live results from NetSuite SuiteAnalytics data Querying live data from LibreChat

At this point, your LibreChat instance communicates with the Connect AI MCP Server and retrieves live NetSuite SuiteAnalytics data through remote MCP tools directly from the chat interface.

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