Integrating Gumloop with Elasticsearch 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 Elasticsearch 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 Elasticsearch 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 Elasticsearch connectivity in Connect AI, register the MCP server in Gumloop, and build a workflow that queries Elasticsearch data.

About Elasticsearch Data Integration

Accessing and integrating live data from Elasticsearch has never been easier with CData. Customers rely on CData connectivity to:

  • Access both the SQL endpoints and REST endpoints, optimizing connectivity and offering more options when it comes to reading and writing Elasticsearch data.
  • Connect to virtually every Elasticsearch instance starting with v2.2 and Open Source Elasticsearch subscriptions.
  • Always receive a relevance score for the query results without explicitly requiring the SCORE() function, simplifying access from 3rd party tools and easily seeing how the query results rank in text relevance.
  • Search through multiple indices, relying on Elasticsearch to manage and process the query and results instead of the client machine.

Users frequently integrate Elasticsearch data with analytics tools such as Crystal Reports, Power BI, and Excel, and leverage our tools to enable a single, federated access layer to all of their data sources, including Elasticsearch.

For more information on CData's Elasticsearch solutions, check out our Knowledge Base article: CData Elasticsearch Driver Features & Differentiators.


Getting Started


Step 1: Configure Elasticsearch Connectivity for Gumloop

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

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

    Set the Server and Port connection properties to connect. To authenticate, set the User and Password properties, PKI (public key infrastructure) properties, or both. To use PKI, set the SSLClientCert, SSLClientCertType, SSLClientCertSubject, and SSLClientCertPassword properties.

    The data provider uses X-Pack Security for TLS/SSL and authentication. To connect over TLS/SSL, prefix the Server value with 'https://'. Note: TLS/SSL and client authentication must be enabled on X-Pack to use PKI.

    Once the data provider is connected, X-Pack will then perform user authentication and grant role permissions based on the realms you have configured.

  4. Click Save & Test
  5. Navigate to the Permissions tab in the Add Elasticsearch 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 Elasticsearch connection configured and a PAT generated, Gumloop is prepared to connect to Elasticsearch 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. Provide the following details:
    • URL: https://mcp.cloud.cdata.com/mcp
    • Label: A descriptive name such as Elasticsearch-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 Elasticsearch data 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 Elasticsearch 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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