Integrating Gumloop with JSON Services via CData Connect AI

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 JSON services.

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 JSON connectivity in Connect AI, register the MCP server in Gumloop, and build a workflow that queries JSON services.

Step 1: Configure JSON Connectivity for Gumloop

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

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "JSON" from the Add Connection panel

3. Enter the necessary authentication properties to connect to JSON.

   See the Getting Started chapter in the data provider documentation to authenticate to your data source: The data provider models JSON APIs as bidirectional database tables and JSON files as read-only views (local files, files stored on popular cloud services, and FTP servers). The major authentication schemes are supported, including HTTP Basic, Digest, NTLM, OAuth, and FTP. See the Getting Started chapter in the data provider documentation for authentication guides.

   After setting the URI and providing any authentication values, set DataModel to more closely match the data representation to the structure of your data.

   The DataModel property is the controlling property over how your data is represented into tables and toggles the following basic configurations.

   • Document (default): Model a top-level, document view of your JSON data. The data provider returns nested elements as aggregates of data.
   • FlattenedDocuments: Implicitly join nested documents and their parents into a single table.
   • Relational: Return individual, related tables from hierarchical data. The tables contain a primary key and a foreign key that links to the parent document.

   See the Modeling JSON Data chapter for more information on configuring the relational representation. You will also find the sample data used in the following examples. The data includes entries for people, the cars they own, and various maintenance services performed on those cars.

   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add JSON Connection page and update the User-based 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.
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 JSON connection configured and a PAT generated, Gumloop is prepared to connect to JSON services 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. Provide the following details:
   • URL: https://mcp.cloud.cdata.com/mcp
   • Label: A descriptive name such as JSON-mcp-server
   • Access Token / API Key: leave blank
   • Additional Header: Authorization: Basic YOUR EMAIL:YOUR PAT
   
   • Save the credentials
   

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

Step 3: Build a workflow and explore live JSON services with Gumloop

1. Visit Gumloop Personal workspace and click on the Create Flow

2. Select the icon or press Ctrl + B to add a node or a subflow

3. Search for Ask AI and select it

4. Click Show More Options and enable the Connect MCP Server? option

5. From the MCP Servers dropdown, choose the saved MCP credential
6. Add a Prompt and Choose an AI Model according to your requirements

7. After configuring the required details, Click Run to run the pipeline

With the workflow run completed, Gumloop demonstrates successful retrieval of JSON services 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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