Integrating Gumloop with Harvest Data via CData Connect AI

Yazhini G
Yazhini G
Technical Marketing Engineer
Leverage the CData Connect AI Remote MCP Server to enable Gumloop to securely access and act on Harvest 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 Harvest 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 Harvest connectivity in Connect AI, register the MCP server in Gumloop, and build a workflow that queries Harvest data.

Step 1: Configure Harvest Connectivity for Gumloop

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

  1. Log into Connect AI, click Sources, and then click Add Connection
  2. Adding a Connection
  3. Select "Harvest" from the Add Connection panel
  4. Selecting a data source
  5. Enter the necessary authentication properties to connect to Harvest.

    Start by setting the Profile connection property to the location of the Harvest Profile on disk (e.g. C:\profiles\Harvest.apip). Next, set the ProfileSettings connection property to the connection string for Harvest (see below).

    Harvest API Profile Settings

    To authenticate to Harvest, you can use either Token authentication or the OAuth standard. Use Basic authentication to connect to your own data. Use OAuth to allow other users to connect to their data.

    Using Token Authentication

    To use Token Authentication, set the APIKey to your Harvest Personal Access Token in the ProfileSettings connection property. In addition to APIKey, set your AccountId in ProfileSettings to connect.

    Using OAuth Authentication

    First, register an OAuth2 application with Harvest. The application can be created from the "Developers" section of Harvest ID.

    After setting the following connection properties, you are ready to connect:

    • ProfileSettings: Set your AccountId in ProfileSettings.
    • AuthScheme: Set this to OAuth.
    • OAuthClientId: Set this to the client ID that you specified in your app settings.
    • OAuthClientSecret: Set this to the client secret that you specified in your app settings.
    • CallbackURL: Set this to the Redirect URI that you specified in your app settings.
    • InitiateOAuth: Set this to GETANDREFRESH. You can use InitiateOAuth to manage how the driver obtains and refreshes the OAuthAccessToken.
    Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab in the Add Harvest Connection page and update the User-based permissions. 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 Personal Access Tokens section and click Create PAT.
  3. Give the PAT a name and click Create. 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 Harvest connection configured and a PAT generated, Gumloop is prepared to connect to Harvest 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. Configuring MCP server MCP server app
  5. Provide the following details:
    • URL: https://mcp.cloud.cdata.com/mcp
    • Label: A descriptive name such as Harvest-mcp-server
    • Access Token / API Key: leave blank
    • Additional Header: Authorization: Basic YOUR EMAIL:YOUR PAT
    • Configuring to CData MCP server
    • Save the credentials
    • Saved MCP Credentials

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

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

  1. Visit Gumloop Personal workspace and click on the Create Flow
  2. Create Gumloop workflow
  3. Select the icon or press Ctrl + B to add a node or a subflow
  4. Add a node
  5. Search for Ask AI and select it
  6. Select Ask AI
  7. Click Show More Options and enable the Connect MCP Server? option
  8. Enable
  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. Add Prompt
  12. After configuring the required details, Click Run to run the pipeline
  13. Example 1: Gumloop workflow execution Example 2: Gumloop workflow execution

With the workflow run completed, Gumloop demonstrates successful retrieval of Harvest 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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