【MCP Server】SAS xpt × Claude Desktop 連携ガイド | AI でデータを徹底活用

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 SASxpt, configuring the connection to SAS xpt, 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 SASxpt
2. Configure the connection to SAS xpt
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 SASxpt.
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 SAS xpt.

Step 2: Configure the connection to SAS xpt

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. "cdatasasxpt") 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 SAS xpt

   ローカルSASXpt ファイルへの接続

   URI をSASXpt ファイルを格納しているフォルダに設定すると、ローカルのSASXpt ファイルに接続できます。

   S3 データソースへの接続

   Amazon S3 ソースに接続してSASXpt ファイルを読み込むことができます。以下のプロパティを設定して接続します：

   • URI：接続するバケット内のフォルダに設定。
   • AWSAccessKey：AWS アカウントのアクセスキーに設定。
   • AWSSecretKey：AWS アカウントのシークレットキーに設定。
   • TemporaryLocalFolder：SASXptファイルを一時的にダウンロードするために使用するフォルダへのパス、またはURI に設定。

   Azure Data Lake Storage Gen2 への接続

   ADLS Gen2 に接続してSASXpt ファイルを読み込むことができます。以下のプロパティを設定して接続します：

   • URI：ファイルシステムの名前およびSASXpt ファイルにコンタクトするフォルダの名前に設定。
   • AzureAccount：Azure Data Lake storage アカウントの名前に設定。
   • AzureAccessKey：Azure Data Lake storage Gen 2 ストレージアカウントのアクセスキーに設定。
   • TemporaryLocalFolder：SASXptファイルを一時的にダウンロードするために使用するフォルダへのパス、またはURI に設定。

   Enter the appropriate connection properties in the configuration wizard.

   
5. Click "Connect" to authenticate with SAS xpt.
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 SAS xpt のデータ

Now that we have installed the CData MCP Server and configured a connection, we are ready to start with SAS xpt のデータ 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 SAS xpt のデータ. For example: "Can you give me a quantitative analysis about my closed-won opportunities by industry?"

   NOTE: Claude may need to explore the SAS xpt のデータ 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.