How to Connect to Live Sybase 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 Sybase data in real-time through natural language queries. This article outlines the process of connecting to Sybase using Connect AI Remote MCP and configuring Gemini CLI to interact with your Sybase data.
CData Connect AI offers a dedicated cloud-to-cloud interface for connecting to Sybase data. The CData Connect AI Remote MCP Server enables secure communication between Gemini CLI and Sybase. This allows you to ask questions and take actions on your Sybase 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 Sybase. This leverages server-side processing to swiftly deliver the requested Sybase 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 Sybase data, plus hundreds of other sources.
Step 1: Configure Sybase Connectivity for Gemini CLI
Connectivity to Sybase from Gemini CLI is made possible through CData Connect AI Remote MCP. To interact with Sybase data from Gemini CLI, we start by creating and configuring a Sybase connection in CData Connect AI.
- Log into Connect AI, click Sources, and then click Add Connection
- Select "Sybase" from the Add Connection panel
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Enter the necessary authentication properties to connect to Sybase.
To connect to Sybase, specify the following connection properties:
- Server: Set this to the name or network address of the Sybase database instance.
- Database: Set this to the name of the Sybase database running on the specified Server.
Optionally, you can also secure your connections with TLS/SSL by setting UseSSL to true.
Sybase supports several methods for authentication including Password and Kerberos.
Connect Using Password Authentication
Set the AuthScheme to Password and set the following connection properties to use Sybase authentication.
- User: Set this to the username of the authenticating Sybase user.
- Password: Set this to the username of the authenticating Sybase user.
Connect using LDAP Authentication
To connect with LDAP authentication, configure Sybase server-side to use the LDAP authentication mechanism.
After configuring Sybase for LDAP, you can connect using the same credentials as Password authentication.
Connect Using Kerberos Authentication
To leverage Kerberos authentication, begin by enabling it setting AuthScheme to Kerberos. See the Using Kerberos section in the Help documentation for more information on using Kerberos authentication.
You can find an example connection string below:
Server=MyServer;Port=MyPort;User=SampleUser;Password=SamplePassword;Database=MyDB;Kerberos=true;KerberosKDC=MyKDC;KerberosRealm=MYREALM.COM;KerberosSPN=server-name
- Click Save & Test
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Navigate to the Permissions tab in the Add Sybase Connection page and update the User-based 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.
- Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
- On the Settings page, go to the Access Tokens section and click Create PAT.
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Give the PAT a name and click Create.
- 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 Sybase 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:
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Ensure Gemini CLI is installed on your system. If not, install it using npm:
npm install -g @google-gemini/cli
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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
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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..."
- Save the settings file. Gemini CLI will now use the CData Connect AI MCP Server for data operations.
Step 3: Query Live Sybase Data with Natural Language
With Gemini CLI configured and connected to CData Connect AI, you can now interact with your Sybase data using natural language queries. The MCP integration allows you to ask questions and receive responses from the Sybase data source in real-time.
Start using Gemini CLI to explore your data:
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Open your terminal and start a Gemini CLI session:
gemini
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You can now use natural language to query your Sybase 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"
- Gemini CLI will automatically translate your natural language queries into appropriate SQL queries and execute them against your Sybase 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 Sybase data without writing complex SQL queries or needing deep technical knowledge of the underlying data structure.
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