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

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

Step 1: Configure CSV Connectivity for Microsoft Copilot Studio

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

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

   Connecting to Local or Cloud-Stored (Box, Google Drive, Amazon S3, SharePoint) CSV Files

   CData Drivers let you work with CSV files stored locally and stored in cloud storage services like Box, Amazon S3, Google Drive, or SharePoint, right where they are.

   Setting connection properties for local files

   Set the URI property to local folder path.

   Setting connection properties for files stored in Amazon S3

   To connect to CSV file(s) within Amazon S3, set the URI property to the URI of the Bucket and Folder where the intended CSV files exist. In addition, at least set these properties:

   • AWSAccessKey: AWS Access Key (username)
   • AWSSecretKey: AWS Secret Key

   Setting connection properties for files stored in Box

   To connect to CSV file(s) within Box, set the URI property to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect to Box.

   Dropbox

   To connect to CSV file(s) within Dropbox, set the URI proprerty to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect to Dropbox. Either User Account or Service Account can be used to authenticate.

   SharePoint Online (SOAP)

   To connect to CSV file(s) within SharePoint with SOAP Schema, set the URI proprerty to the URI of the document library that includes the intended CSV file. Set User, Password, and StorageBaseURL.

   SharePoint Online REST

   To connect to CSV file(s) within SharePoint with REST Schema, set the URI proprerty to the URI of the document library that includes the intended CSV file. StorageBaseURL is optional. If not set, the driver will use the root drive. OAuth is used to authenticate.

   Google Drive

   To connect to CSV file(s) within Google Drive, set the URI property to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect and set InitiateOAuth to GETANDREFRESH.

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

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

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

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

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