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

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 Paylocity data in real-time through natural language queries. This article outlines the process of connecting to Paylocity using Connect AI Remote MCP and configuring Gemini CLI to interact with your Paylocity data.

CData Connect AI offers a dedicated cloud-to-cloud interface for connecting to Paylocity data. The CData Connect AI Remote MCP Server enables secure communication between Gemini CLI and Paylocity. This allows you to ask questions and take actions on your Paylocity 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 Paylocity. This leverages server-side processing to swiftly deliver the requested Paylocity 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 Paylocity data, plus hundreds of other sources.

Step 1: Configure Paylocity Connectivity for Gemini CLI

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

1. Log into Connect AI, click Sources, and then click Add Connection
👁 Adding a Connection

2. Select "Paylocity" from the Add Connection panel
👁 Selecting a data source

3. Enter the necessary authentication properties to connect to Paylocity.

   Set the following to establish a connection to Paylocity:

   • RSAPublicKey: Set this to the RSA Key associated with your Paylocity, if the RSA Encryption is enabled in the Paylocity account.

     This property is required for executing Insert and Update statements, and it is not required if the feature is disabled.

   • UseSandbox: Set to true if you are using sandbox account.
   • CustomFieldsCategory: Set this to the Customfields category. This is required when IncludeCustomFields is set to true. The default value for this property is PayrollAndHR.
   • Key: The AES symmetric key(base 64 encoded) encrypted with the Paylocity Public Key. It is the key used to encrypt the content.

     Paylocity will decrypt the AES key using RSA decryption.
     It is an optional property if the IV value not provided, The driver will generate a key internally.

   • IV: The AES IV (base 64 encoded) used when encrypting the content. It is an optional property if the Key value not provided, The driver will generate an IV internally.

   Connect Using OAuth Authentication

   You must use OAuth to authenticate with Paylocity. OAuth requires the authenticating user to interact with Paylocity using the browser. For more information, refer to the OAuth section in the Help documentation.

   The Pay Entry API

   The Pay Entry API is completely separate from the rest of the Paylocity API. It uses a separate Client ID and Secret, and must be explicitly requested from Paylocity for access to be granted for an account. The Pay Entry API allows you to automatically submit payroll information for individual employees, and little else. Due to the extremely limited nature of what is offered by the Pay Entry API, we have elected not to give it a separate schema, but it may be enabled via the UsePayEntryAPI connection property.

   Please be aware that when setting UsePayEntryAPI to true, you may only use the CreatePayEntryImportBatch & MergePayEntryImportBatchgtable stored procedures, the InputTimeEntry table, and the OAuth stored procedures. Attempts to use other features of the product will result in an error. You must also store your OAuthAccessToken separately, which often means setting a different OAuthSettingsLocation when using this connection property. 👁 Configuring a connection (Salesforce is shown)
   

4. Click Save & Test
5. Navigate to the Permissions tab in the Add Paylocity 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 Paylocity 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-cloud": {
    "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 Paylocity Data with Natural Language

With Gemini CLI configured and connected to CData Connect AI, you can now interact with your Paylocity data using natural language queries. The MCP integration allows you to ask questions and receive responses from the Paylocity 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 Paylocity 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 Paylocity 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 Paylocity data without writing complex SQL queries or needing deep technical knowledge of the underlying data structure.

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