Integrate Goose with Live SQL Analysis Services 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 SQL Analysis Services 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 SQL Analysis Services data. You can list catalogs, explore schemas, and query records from SQL Analysis Services data using natural language prompts, with all data access running securely against authorized sources.

This article explains how to configure SQL Analysis Services 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 SQL Analysis Services data from the Goose chat.

Step 1: Configure SQL Analysis Services connectivity for Goose

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

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

    To connect, provide authentication and set the Url property to a valid SQL Server Analysis Services endpoint. You can connect to SQL Server Analysis Services instances hosted over HTTP with XMLA access. See the Microsoft documentation to configure HTTP access to SQL Server Analysis Services.

    To secure connections and authenticate, set the corresponding connection properties, below. The data provider supports the major authentication schemes, including HTTP and Windows, as well as SSL/TLS.

    • HTTP Authentication

      Set AuthScheme to "Basic" or "Digest" and set User and Password. Specify other authentication values in CustomHeaders.

    • Windows (NTLM)

      Set the Windows User and Password and set AuthScheme to "NTLM".

    • Kerberos and Kerberos Delegation

      To authenticate with Kerberos, set AuthScheme to NEGOTIATE. To use Kerberos delegation, set AuthScheme to KERBEROSDELEGATION. If needed, provide the User, Password, and KerberosSPN. By default, the data provider attempts to communicate with the SPN at the specified Url.

    • SSL/TLS:

      By default, the data provider attempts to negotiate SSL/TLS by checking the server's certificate against the system's trusted certificate store. To specify another certificate, see the SSLServerCert property for the available formats.

    You can then access any cube as a relational table: When you connect the data provider retrieves SSAS metadata and dynamically updates the table schemas. Instead of retrieving metadata every connection, you can set the CacheLocation property to automatically cache to a simple file-based store.

    See the Getting Started section of the CData documentation, under Retrieving Analysis Services Data, to execute SQL-92 queries to the cubes.

    Configuring a connection (Salesforce is shown)
  6. Click Save & Test
  7. Navigate to the Permissions tab and update user-based permissions
  8. 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
  5. Copy the token when displayed and store it securely. It will not be shown again

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

Step 3: Query live SQL Analysis Services data from Goose

With the integration complete, use the Goose chat to interact with live SQL Analysis Services 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 SQL Analysis Services
    • Query the top 5 records from a table in SQL Analysis Services data
  2. Goose calls the Connect AI MCP Server and returns live results from SQL Analysis Services data Querying live data from Goose

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

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