How to Query Live Webex Data in Claude Desktop

Model Context Protocol (MCP) is an emerging, open-source standard for connecting LLMs with external services and data sources. Through MCP Servers, AI clients can perform actions like opening Jira tickets, posting Slack messages, committing GitHub branches and more. With CData MCP Server, these capabilities expand exponentially.

CData MCP Server provides schema-aware context to AI tools — whether you're using it for AI-assisted code generation in IDEs like Cursor, or for querying live data through chat interfaces like Claude Desktop.

In this article, we guide the reader through installing CData API Driver for MCP Server, configuring the connection to Webex, and asking questions of the data in Claude Desktop.

Prerequisites

You need to download Claude Desktop (download) and create an account before continuing.

Overview

Here's a quick overview of the steps:

1. Download and install the CData API Driver for MCP Server
2. Configure the connection to Webex
3. Ask questions about the data in Claude Desktop

Step 1: Download and install CData MCP Server

1. To begin, navigate to https://www.cdata.com/solutions/codeassist/ and download the CData API Driver for MCP Server. 👁 Downloading the CData MCP Server installer
   
2. Find and double-click the installer to begin the installation. 👁 Running the installer for CData MCP Server (Google Sheets is shown.)
   
3. Follow the prompts to complete the installation. 👁 Completing the CData MCP Server installation (Google Sheets is shown).
   

When the installation is complete, you are ready to configure MCP Server by connecting to Webex.

Step 2: Configure the connection to Webex

1. After installation, the MCP Server configuration wizard should open automatically. 👁 The MCP Server configuration wizard.
   

   NOTE: If the wizard does not open automatically, search for "CData MCP Server" in the Windows search bar and double-click the application. 👁 Opening the MCP Server configuration wizard (Google Sheets is shown).
   

2. Click the dropdown menu in MCP Configuration > Configuration Name and select "
3. Name the configuration (e.g. "cdataapi") and click "OK."

   NOTE: This name is used as the name for the MCP server and as the prefix for all of the MCP Server's tools.

   👁 Naming the configuration.
   

4. Connecting to Webex

   To authenticate to Webex, and connect to your own data or to allow other users to connect to their data, you can use the OAuth standard.

   Using OAuth Authentication

   First, you will need to register an OAuth application with Webex. To do so, navigate to the Webex Developer Portal and create a new integration. Your OAuth application will be assigned a client id and a client secret.

   After setting the following connection properties, you are ready to connect:

   • AuthScheme: Set this to OAuth.
   • InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage the process to obtain the OAuthAccessToken.
   • OAuthClientId: Set this to the client_id that is specified in your app settings.
   • OAuthClientSecret: Set this to the client_secret that is specified in your app settings.
   • CallbackURL: Set this to the Redirect URI that is specified in your app settings.
   • Scope: Set this in ProfileSettings to specify the OAuth scopes requested during authorization. Multiple scopes can be space-separated (e.g. ProfileSettings='Scope=spark:all spark:kms').

   Example connection string:

   Profile=C:\profiles\Webex.apip;Authscheme=OAuth;InitiateOAuth=GETANDREFRESH;OAuthClientId=your_client_id;OAuthClientSecret=your_client_secret;CallbackUrl=your_callback_url;ProfileSettings='Scope=your_scopes';
   

   Enter the appropriate connection properties in the configuration wizard.

   👁 Configuring the Server to connect with a specific Spreadsheet.
   

5. Click "Connect" to authenticate with Webex through OAuth. 👁 Authenticating with Google
   

   NOTE: The configuration wizard should open your browser and ask you to sign into Webex. If your browser does not open, close the configuration wizard and re-open the application using "Run as Administrator" (see below).

   👁 Running the configuration wizard with elevated permissions.
   
6. Finally, click "Save Configuration" to save the configuration. 👁 Saving the MCP Server configuration.
   

   NOTE: This saves the configuration details to a separate file and updates the Claude Desktop configuration file (claude_desktop_config.json) to start MCP Server when the Claude Desktop client starts.

With MCP Server configured, you are ready to start asking questions of your live data from Claude.

Step 3: Ask AI for answers from live Webex data

Now that we have installed MCP Server and configured a connection, we are ready to start with Webex data in Claude Desktop.

1. Open Claude Desktop. It may take a moment for MCP Server to start, but you will see the list of servers and tools available in the Claude interface (look for the settings icon below the prompt bar). 👁 The MCP servers menu showing available connections in Claude Desktop
   

   You can individually enable and disable specific tools by clicking on the server name. 👁 The expanded tool list for MCP Server in Claude Desktop
   

2. Now that you have connected, you can ask Claude questions about the Webex data. For example: "Can you give me a quantitative analysis about my closed-won opportunities by industry?"

   NOTE: Claude may need to explore the Webex data to make sense of it before it can begin answering questions of the data. The tabular model presented by CData alongside the database tools available simplify the data exploration and analysis for an LLM.

   👁 Claude Desktop displaying a quantitative analysis of live data
   

Build with MCP Server. Deploy with CData Drivers.

Download CData API Driver for MCP Server for free and give your AI tools schema-aware access to live Webex data during development. When you're ready to move to production, CData API Drivers deliver the same SQL-based access with enterprise-grade performance, security, and reliability.

Visit the CData Community to share insights, ask questions, and explore what's possible with MCP-powered AI workflows.