How to Connect to Live TaxJar Data from Gemini CLI (via CData Connect AI)

Jerod Johnson
Jerod Johnson
Director, Technology Evangelism
Leverage the CData Connect AI Remote MCP Server to enable Gemini CLI to securely read and take actions on your TaxJar data for you.

Gemini CLI is a command-line interface tool that provides direct access to Google's Gemini AI models for code generation, text analysis, and conversational AI capabilities. When combined with CData Connect AI Remote MCP, you can leverage Gemini CLI to interact with your TaxJar data in real-time through natural language queries. This article outlines the process of connecting to TaxJar using Connect AI Remote MCP and configuring Gemini CLI to interact with your TaxJar data.

CData Connect AI offers a dedicated cloud-to-cloud interface for connecting to TaxJar data. The CData Connect AI Remote MCP Server enables secure communication between Gemini CLI and TaxJar. This allows you to ask questions and take actions on your TaxJar data using natural language through Gemini CLI, all without the need for data replication to a natively supported database. With its inherent optimized data processing capabilities, CData Connect AI efficiently channels all supported SQL operations, including filters and JOINs, directly to TaxJar. This leverages server-side processing to swiftly deliver the requested TaxJar data.

In this article, we show how to configure Gemini CLI to conversationally explore (or Vibe Query) your data using natural language. With Connect AI you can query and interact with live TaxJar data, plus hundreds of other sources.

Step 1: Configure TaxJar Connectivity for Gemini CLI

Connectivity to TaxJar from Gemini CLI is made possible through CData Connect AI Remote MCP. To interact with TaxJar data from Gemini CLI, we start by creating and configuring a TaxJar connection in CData Connect AI.

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

    To authenticate to the TaxJar API, first obtain the API Key from the TaxJar UI.

    NOTE: the API is available only for Professional and Premium TaxJar plans.

    If you already have a Professional or Premium plan you can find the API Key by logging in the TaxJar UI and navigating to Account -> TaxJar API. After obtaining the API Key, you can set it in the APIKey connection property.

    Additional Notes

    • By default, the CData connector will retrieve data of the last 3 months in cases where the entity support date range filtering. You can set StartDate to specify the minimum creation date of the data retrieved.
    • If the API Key has been created for a sandbox API account please set UseSandbox to true, but not all endpoints will work as expected. For more information, refer to the TaxJar developer documentation.
    Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab in the Add TaxJar Connection page and update the User-based permissions. Updating permissions

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Gemini CLI. It is best practice to create a separate PAT for each service to maintain granularity of access.

  1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
  2. On the Settings page, go to the Access Tokens section and click Create PAT.
  3. Give the PAT a name and click Create. Creating a new PAT
  4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, we are ready to connect to TaxJar data from Gemini CLI.

Step 2: Configure Gemini CLI for CData Connect AI

Follow these steps to configure Gemini CLI to connect to CData Connect AI:

  1. Ensure Gemini CLI is installed on your system. If not, install it using npm:
    npm install -g @google-gemini/cli
  2. Locate your Gemini CLI settings file. If the file doesn't exist, create it:
    • Linux/Unix/Mac: ~/.gemini/settings.json
    • Windows: %USERPROFILE%\.gemini\settings.json
  3. Add the CData Connect AI Remote MCP Server to the mcpServers object in your settings file. Replace YOUR_EMAIL and YOUR_PAT with your Connect AI email address and the PAT created previously:
    
    {
      "mcpServers": {
        "cdata-connect-ai": {
          "httpUrl": "https://mcp.cloud.cdata.com/mcp",
          "headers": {
            "Authorization": "Basic YOUR_EMAIL:YOUR_PAT"
          }
        }
      }
    }    
    For example, if your email is [email protected] and your PAT is Uu90pt5vEO..., the Authorization header would be:
    "Authorization": "Basic [email protected]:Uu90pt5vEO..."
  4. Save the settings file. Gemini CLI will now use the CData Connect AI MCP Server for data operations.

Step 3: Query Live TaxJar Data with Natural Language

With Gemini CLI configured and connected to CData Connect AI, you can now interact with your TaxJar data using natural language queries. The MCP integration allows you to ask questions and receive responses from the TaxJar data source in real-time.

Start using Gemini CLI to explore your data:

  1. Open your terminal and start a Gemini CLI session:
    gemini
  2. You can now use natural language to query your TaxJar data. For example:
    • "Show me all customers from the last 30 days"
    • "What are my top performing products?"
    • "Analyze sales trends for Q4"
    • "List all active projects with their current status"
  3. Gemini CLI will automatically translate your natural language queries into appropriate SQL queries and execute them against your TaxJar data through the CData Connect AI MCP Server.

The combination of Gemini CLI's natural language processing capabilities and CData Connect AI's robust data connectivity enables you to explore and analyze your TaxJar data without writing complex SQL queries or needing deep technical knowledge of the underlying data structure.

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