How to Query Live SAP Fieldglass 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 Servers, these capabilities expand exponentially.

In this article, we guide the reader through installing the CData MCP Server for SAP Fieldglass, configuring the connection to SAP Fieldglass, 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 MCP Server for SAP Fieldglass
2. Configure the connection to SAP Fieldglass
3. Ask questions about the data in Claude Desktop

Step 1: Download and install the CData MCP Server

1. To begin, navigate to https://www.cdata.com/solutions/mcp/connectors and download the CData MCP Server for SAP Fieldglass.
2. Find and double-click the installer to begin the installation.
3. Follow the prompts to complete the installation.

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

Step 2: Configure the connection to SAP Fieldglass

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

   NOTE: If the wizard does not open automatically, search for "CData MCP Server" in the Windows search bar and double-click the application.

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

   

4. Connecting to SAP Fieldglass

   To authenticate, specify the Username, Password, APIKey, and EnvironmentURL connection properties.

   To obtain an APIKey, log in to the SAP API Business Hub and click on Get API Key.

   Enter the appropriate connection properties in the configuration wizard.

   
5. Click "Connect" to authenticate with SAP Fieldglass through OAuth.

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

   
6. Finally, click "Save Configuration" to save the MCP server.

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

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

Step 3: Ask AI for answers from live SAP Fieldglass data

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

1. Open Claude Desktop. It may take a moment for the MCP Servers 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).

   You can individually enable and disable specific tools by clicking on the server name.

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

   NOTE: Claude may need to explore the SAP Fieldglass 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.

   

Connect your AI to your data today!

CData MCP Servers make it easier than ever for LLMs to work with live enterprise data. To explore the technology hands-on, download a free, 30-day trial or visit the CData Community to share insights, ask questions, and help shape the future of enterprise-ready AI.