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

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

Step 1: Configure Azure Table Connectivity for Microsoft Copilot Studio

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

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

   Specify your AccessKey and your Account to connect. Set the Account property to the Storage Account Name and set AccessKey to one of the Access Keys. Either the Primary or Secondary Access Keys can be used. To obtain these values, navigate to the Storage Accounts blade in the Azure portal. You can obtain the access key by selecting your account and clicking Access Keys in the Settings section.

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

With the connection configured, we are ready to connect to Azure Table 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 Azure Table Data with Microsoft Copilot Studio

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

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

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