Integrate Goose with Live CSV Data via CData Connect AI
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 CSV data. You can list catalogs, explore schemas, and query records from CSV data using natural language prompts, with all data access running securely against authorized sources.
This article explains how to configure CSV 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 CSV data from the Goose chat.
Step 1: Configure CSV connectivity for Goose
Connectivity to CSV from Goose is made possible through Connect AI's Remote MCP Server. To interact with CSV data from Goose, start by creating and configuring a CSV connection in Connect AI.
- Log into Connect AI, click Sources, and then click Add Connection
- Select CSV from the Add Connection panel
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Enter the necessary authentication properties to connect to CSV.
Connecting to Local or Cloud-Stored (Box, Google Drive, Amazon S3, SharePoint) CSV Files
CData Drivers let you work with CSV files stored locally and stored in cloud storage services like Box, Amazon S3, Google Drive, or SharePoint, right where they are.
Setting connection properties for local files
Set the URI property to local folder path.
Setting connection properties for files stored in Amazon S3
To connect to CSV file(s) within Amazon S3, set the URI property to the URI of the Bucket and Folder where the intended CSV files exist. In addition, at least set these properties:
- AWSAccessKey: AWS Access Key (username)
- AWSSecretKey: AWS Secret Key
Setting connection properties for files stored in Box
To connect to CSV file(s) within Box, set the URI property to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect to Box.
Dropbox
To connect to CSV file(s) within Dropbox, set the URI proprerty to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect to Dropbox. Either User Account or Service Account can be used to authenticate.
SharePoint Online (SOAP)
To connect to CSV file(s) within SharePoint with SOAP Schema, set the URI proprerty to the URI of the document library that includes the intended CSV file. Set User, Password, and StorageBaseURL.
SharePoint Online REST
To connect to CSV file(s) within SharePoint with REST Schema, set the URI proprerty to the URI of the document library that includes the intended CSV file. StorageBaseURL is optional. If not set, the driver will use the root drive. OAuth is used to authenticate.
Google Drive
To connect to CSV file(s) within Google Drive, set the URI property to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect and set InitiateOAuth to GETANDREFRESH.
- Click Save & Test
- Navigate to the Permissions tab and update user-based 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.
- Click the gear icon () at the top right of the Connect AI app to open Settings
- On the Settings page, go to the Access Tokens section and click Create PAT
- Give the PAT a descriptive name and click Create
- Copy the token when displayed and store it securely. It will not be shown again
With the CSV connection configured and a PAT generated, Goose can now connect to CSV 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.
- Download and install Goose by following the official installation guide, then launch the application
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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
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In the left navigation, click Extensions, then click + Add custom extension
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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
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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==
- Click Save to save the configuration
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Return to the chat, click the extensions icon at the bottom of the chat input, and confirm that the configured MCP is enabled
With the MCP server added and an LLM provider configured, Goose is ready to query live CSV data through Connect AI.
Step 3: Query live CSV data from Goose
With the integration complete, use the Goose chat to interact with live CSV data through natural language prompts handled by the configured LLM.
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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 CSV
- Query the top 5 records from a table in CSV data
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Goose calls the Connect AI MCP Server and returns live results from CSV data
At this point, your Goose agent communicates with the Connect AI MCP Server and retrieves live CSV data through remote MCP tools directly from the chat.
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