Use Microsoft Copilot Studio to talk to your SQL Analysis Services 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 SQL Analysis Services data in real-time. This article outlines the process of connecting to SQL Analysis Services using Connect AI Remote MCP and creating a connection in Copilot Studio to interact with your SQL Analysis Services data.

CData Connect AI offers a dedicated cloud-to-cloud interface for connecting to SQL Analysis Services data. The CData Connect AI Remote MCP Server enables secure communication between Microsoft Copilot Studio and SQL Analysis Services. This allows you to ask questions and take actions on your SQL Analysis Services 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 SQL Analysis Services. This leverages server-side processing to swiftly deliver the requested SQL Analysis Services 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 SQL Analysis Services data, plus hundreds of other sources.

Step 1: Configure SQL Analysis Services Connectivity for Microsoft Copilot Studio

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

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

   To connect, provide authentication and set the Url property to a valid SQL Server Analysis Services endpoint. You can connect to SQL Server Analysis Services instances hosted over HTTP with XMLA access. See the Microsoft documentation to configure HTTP access to SQL Server Analysis Services.

   To secure connections and authenticate, set the corresponding connection properties, below. The data provider supports the major authentication schemes, including HTTP and Windows, as well as SSL/TLS.

   • HTTP Authentication

     Set AuthScheme to "Basic" or "Digest" and set User and Password. Specify other authentication values in CustomHeaders.

   • Windows (NTLM)

     Set the Windows User and Password and set AuthScheme to "NTLM".

   • Kerberos and Kerberos Delegation

     To authenticate with Kerberos, set AuthScheme to NEGOTIATE. To use Kerberos delegation, set AuthScheme to KERBEROSDELEGATION. If needed, provide the User, Password, and KerberosSPN. By default, the data provider attempts to communicate with the SPN at the specified Url.

   • SSL/TLS:

     By default, the data provider attempts to negotiate SSL/TLS by checking the server's certificate against the system's trusted certificate store. To specify another certificate, see the SSLServerCert property for the available formats.

   You can then access any cube as a relational table: When you connect the data provider retrieves SSAS metadata and dynamically updates the table schemas. Instead of retrieving metadata every connection, you can set the CacheLocation property to automatically cache to a simple file-based store.

   See the Getting Started section of the CData documentation, under Retrieving Analysis Services Data, to execute SQL-92 queries to the cubes.

   Click Save & Test
4. Navigate to the Permissions tab in the Add SQL Analysis Services Connection page and update the User-based permissions.

With the connection configured, we are ready to connect to SQL Analysis Services 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 SQL Analysis Services Data with Microsoft Copilot Studio

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

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

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