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URL: https://www.cdata.com/kb/tech/gsheets-cloud-gumloop.rst

⇱ Integrating Gumloop with Google Sheets Data via CData Connect AI


Integrating Gumloop with Google Sheets Data via CData Connect AI

πŸ‘ Yazhini G
Yazhini G
Technical Marketing Engineer
Leverage the CData Connect AI Remote MCP Server to enable Gumloop to securely access and act on Google Sheets data within automated workflows.

Gumloop is a visual automation platform designed to create AI-powered workflows by combining triggers, AI nodes, APIs, and data connectors. By integrating Gumloop with CData Connect AI through the built-in MCP (Model Context Protocol) Server, workflows can seamlessly access and interact with live Google Sheets data.

The platform provides a low-code environment, making it easier to orchestrate complex processes without heavy development effort. Its flexibility allows integration across multiple business applications, enabling end-to-end automation with live data.

This article outlines the steps required to configure Google Sheets connectivity in Connect AI, register the MCP server in Gumloop, and build a workflow that queries Google Sheets data.

Step 1: Configure Google Sheets Connectivity for Gumloop

Connectivity to Google Sheets from Gumloop is made possible through CData Connect AI's Remote MCP Server. To interact with Google Sheets data from Gumloop, we start by creating and configuring a Google Sheets connection in CData Connect AI.

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. πŸ‘ Adding a Connection
  3. Select "Google Sheets" from the Add Connection panel
  4. πŸ‘ Selecting a data source
  5. Google Sheets uses OAuth to authenticate. Click "Sign in" to authenticate with Google Sheets. πŸ‘ Authenticating with OAuth (Salesforce is shown).
  6. Navigate to the Permissions tab in the Add Google Sheets Connection page and update the User-based permissions. πŸ‘ Updating permissions

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Gumloop. It is best practice to create a separate PAT for each service to maintain granularity of access.

  1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
  2. On the Settings page, go to the Access Tokens section and click Create PAT.
  3. Give the PAT a name and click Create. πŸ‘ Creating a new PAT
  4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the Google Sheets connection configured and a PAT generated, Gumloop is prepared to connect to Google Sheets data through the CData MCP server.

Step 2: Connect to the MCP server in Gumloop

The MCP server endpoint and authentication values from Connect AI must be added to Gumloop credentials.

  1. Sign in to Gumloop and create an account
  2. Visit the Gumloop Credentials page to configure MCP server
  3. Click on Add Credentials and search and select MCP Server
  4. πŸ‘ Configuring MCP server
    πŸ‘ MCP server app
  5. Provide the following details:

The MCP server is now available to build workflows in Gumloop.

Step 3: Build a workflow and explore live Google Sheets data with Gumloop

  1. Visit Gumloop Personal workspace and click on the Create Flow
  2. πŸ‘ Create Gumloop workflow
  3. Select the icon or press Ctrl + B to add a node or a subflow
  4. πŸ‘ Add a node
  5. Search for Ask AI and select it
  6. πŸ‘ Select Ask AI
  7. Click Show More Options and enable the Connect MCP Server? option
  8. πŸ‘ Enable 'Connect MCP Server?'
  9. From the MCP Servers dropdown, choose the saved MCP credential
  10. Add a Prompt and Choose an AI Model according to your requirements
  11. πŸ‘ Add Prompt
  12. After configuring the required details, Click Run to run the pipeline
  13. πŸ‘ Example 1: Gumloop workflow execution
    πŸ‘ Example 2: Gumloop workflow execution

With the workflow run completed, Gumloop demonstrates successful retrieval of Google Sheets data through the CData Connect AI MCP server, with the MCP Client node providing the ability to ask questions, retrieve records, and perform actions on the data.

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