Integrate Goose with Live Elasticsearch Data via CData Connect AI

Yazhini G
Yazhini G
Technical Marketing Engineer
Leverage the CData Connect AI Remote MCP Server to enable Goose to securely access and query live Elasticsearch data from within the local AI agent.

Goose is an open source AI agent that runs locally on your machine and works with a wide range of LLM providers. It supports the model context protocol (MCP) through its extensions framework, so you can add external tools and data sources and give the agent access to live systems beyond the model's training data.

By integrating Goose with CData Connect AI through the built-in MCP Server, Goose gains governed, real-time access to live Elasticsearch data. You can list catalogs, explore schemas, and query records from Elasticsearch data using natural language prompts, with all data access running securely against authorized sources.

This article explains how to configure Elasticsearch connectivity in Connect AI, generate the required personal access token, install and set up Goose, add the Connect AI MCP Server as a custom extension, and verify the integration by querying live Elasticsearch data from the Goose chat.

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 Goose

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

  1. Log into Connect AI, click Sources, and then click Add Connection
    2. Adding a connection in Connect AI
  2. Select Elasticsearch from the Add Connection panel
    3. Selecting data source
  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.

    Configuring a connection (Salesforce is shown)
  4. Click Save & Test
  5. Navigate to the Permissions tab and update user-based permissions
    6. Updating permissions

Add a Personal Access Token

A Personal Access Token (PAT) is used to authenticate the connection to Connect AI from Goose. It is best practice to create a separate PAT for each integration to maintain granular access control.

  1. Click the gear icon () at the top right of the Connect AI app to open Settings
  2. On the Settings page, go to the Access Tokens section and click Create PAT
  3. Give the PAT a descriptive name and click Create
    4. Creating a new PAT
  4. Copy the token when displayed and store it securely. It will not be shown again

With the Elasticsearch connection configured and a PAT generated, Goose can now connect to Elasticsearch data through Connect AI.

Step 2: Install and set up Goose

Next, install Goose, choose an LLM provider, and add the Connect AI Remote MCP Server as a custom extension so the agent can discover and call live data tools through Connect AI.

  1. Download and install Goose by following the official installation guide, then launch the application
  2. On the Welcome to goose screen, choose an AI provider. Select Use Free/Local Providers to run a local model, or Connect to a Provider to configure a provider such as OpenAI, Anthropic, or Google, and enter the required API key Choosing an AI provider in Goose
  3. In the left navigation, click Extensions, then click + Add custom extension Adding a custom extension in Goose
  4. In the extension dialog, configure the server with the following values:
    • Extension Name: CData MCP, or any name of your choice
    • Type: Streamable HTTP
    • Endpoint: https://mcp.cloud.cdata.com/mcp
  5. Under Request Headers, add the following two headers and click + Add after each pair:
    • Authorization: Basic your_base64_encoded_email_PAT
    • Content-Type: application/json

    Note: Goose will use Basic authentication with Connect AI. Combine your Connect AI user email and the PAT you created earlier in the format email:PAT, base64 encode the combined string, and prefix it with Basic. For example, given [email protected]:ABC123...XYZ789, the Authorization header value becomes something like: Basic dXNlckBkb21haW4uY29tOkFCQzEyMy4uLlhZWjc4OQ==

    Configuring the Connect AI MCP Server in Goose
  6. Click Save to save the configuration
  7. Return to the chat, click the extensions icon at the bottom of the chat input, and confirm that the configured MCP is enabled Enabling the CData MCP extension in the chat

With the MCP server added and an LLM provider configured, Goose is ready to query live Elasticsearch data through Connect AI.

Step 3: Query live Elasticsearch data from Goose

With the integration complete, use the Goose chat to interact with live Elasticsearch data through natural language prompts handled by the configured LLM.

  1. With the CData MCP extension enabled, type a prompt in the chat, for example:
    • List catalogs from my CData MCP
    • Show the available schemas and tables for Elasticsearch
    • Query the top 5 records from a table in Elasticsearch data
  2. Goose calls the Connect AI MCP Server and returns live results from Elasticsearch data Querying live data from Goose

At this point, your Goose agent communicates with the Connect AI MCP Server and retrieves live Elasticsearch data through remote MCP tools directly from the chat.

Get CData Connect AI

To access hundreds of SaaS, big data, and NoSQL sources directly from your cloud applications, try CData Connect AI today. Download a free 14-day trial of CData Connect AI, and our Support Team is available to help with any questions you have.

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