Use Microsoft Copilot Studio to talk to your SAS Data Sets Data via CData Connect AI

Microsoft Copilot Studio is a no-code/low-code platform for creating AI Agents that can automate tasks, answer questions, and assist with various business processes. When combined with CData Connect AI Remote MCP, you can leverage Copilot Studio to interact with your SAS Data Sets data in real-time. This article outlines the process of connecting to SAS Data Sets using Connect AI Remote MCP and creating a connection in Copilot Studio to interact with your SAS Data Sets data.

CData Connect AI offers a dedicated cloud-to-cloud interface for connecting to SAS Data Sets data. The CData Connect AI Remote MCP Server enables secure communication between Microsoft Copilot Studio and SAS Data Sets. This allows you to ask questions and take actions on your SAS Data Sets data using Microsoft Copilot Studio, 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 SAS Data Sets. This leverages server-side processing to swiftly deliver the requested SAS Data Sets data.

In this article, we show how to build a agent in Microsoft Copilot Studio to conversational explore (or Vibe Query) your data. The connectivity principals apply to any Copilot agent. With Connect AI you can build workflows and agents with access to live SAS Data Sets data, plus hundreds of other sources.

Step 1: Configure SAS Data Sets Connectivity for Microsoft Copilot Studio

Connectivity to SAS Data Sets from Microsoft Copilot Studio is made possible through CData Connect AI Remote MCP. To interact with SAS Data Sets data from Microsoft Copilot Studio, we start by creating and configuring a SAS Data Sets connection in CData Connect AI.

1. Log into Connect AI, click Connections and click Add Connection
2. Select "SAS Data Sets" from the Add Connection panel
3. Enter the necessary authentication properties to connect to SAS Data Sets.

   Set the following connection properties to connect to your SAS DataSet files:

   Connecting to Local Files

   • Set the Connection Type to "Local." Local files support SELECT, INSERT, and DELETE commands.
   • Set the URI to a folder containing SAS files, e.g. C:\PATH\TO\FOLDER\.

   Connecting to Cloud-Hosted SAS DataSet Files

   While the driver is capable of pulling data from SAS DataSet files hosted on a variety of cloud data stores, INSERT, UPDATE, and DELETE are not supported outside of local files in this driver.

   Set the Connection Type to the service hosting your SAS DataSet files. A unique prefix at the beginning of the URI connection property is used to identify the cloud data store and the remainder of the path is a relative path to the desired folder (one table per file) or single file (a single table). For more information, refer to the Getting Started section of the Help documentation.

   Click Save & Test
4. Navigate to the Permissions tab in the Add SAS Data Sets Connection page and update the User-based permissions.

With the connection configured, we are ready to connect to SAS Data Sets data from Microsoft Copilot Studio.

Step 2: Connect Microsoft Copilot Studio to CData Connect AI

Follow these steps to add a CData Connect AI MCP connection in Microsoft Copilot Studio:

1. Under Tools, click Add tool, then click + New Tool.
2. In the Add Tool window, search for and click CData Connect AI.
3. In the Connect to CData Connect AI window, click Create to authenticate your connection CData Connect AI using OAuth authentication.
4. Click Add and configure to add the CData Connect AI Tool to your agent.

Optional: Give the AI Agent context

This step establishes the AI Agent's role and provides context for the conversation through the Instructions property in the Agent. By providing instructions that explicitly informs the agent about its role as an MCP Server expert and lists the available tools, you can enhance the agent's understanding and response accuracy. For example, you can set the System Message to:

You are an expert at using the MCP Client tool connected which is the CData Connect AI MCP Server. Always search thoroughly and use the most relevant MCP Client tool for each query. Below are the available tools and a description of each:
queryData: Execute SQL queries against connected data sources and retrieve results. When you use the queryData tool, ensure you use the following format for the table name: catalog.schema.tableName
getCatalogs: Retrieve a list of available connections from CData Connect AI. The connection names should be used as catalog names in other tools and in any queries to CData Connect AI. Use the `getSchemas` tool to get a list of available schemas for a specific catalog.
getSchemas: Retrieve a list of available database schemas from CData Connect AI for a specific catalog. Use the `getTables` tool to get a list of available tables for a specific catalog and schema.
getTables: Retrieve a list of available database tables from CData Connect AI for a specific catalog and schema. Use the `getColumns` tool to get a list of available columns for a specific table.
getColumns: Retrieve a list of available database columns from CData Connect AI for a specific catalog, schema, and table.
getProcedures: Retrieve a list of stored procedures from CData Connect AI for a specific catalog and schema
getProcedureParameters: Retrieve a list of stored procedure parameters from CData Connect AI for a specific catalog, schema, and procedure.
executeProcedure: Execute stored procedures with parameters against connected data sources
  

Step 3: Explore Live SAS Data Sets Data with Microsoft Copilot Studio

With the Agent created in Microsoft Copilot Studio and the MCP tool connected, you can now interact with your SAS Data Sets data using Microsoft Copilot Studio. The MCP tool allows you to send queries and receive responses from the SAS Data Sets data source in real-time.

Open the chat window in your Microsoft Copilot Studio Agent to begin interacting with your SAS Data Sets data. You can ask questions, retrieve data, and perform actions on your SAS Data Sets data using the MCP tool:

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