Integrate Goose with Live PostgreSQL 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 PostgreSQL data. You can list catalogs, explore schemas, and query records from PostgreSQL data using natural language prompts, with all data access running securely against authorized sources.
This article explains how to configure PostgreSQL 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 PostgreSQL data from the Goose chat.
Step 1: Configure PostgreSQL connectivity for Goose
Connectivity to PostgreSQL from Goose is made possible through Connect AI's Remote MCP Server. To interact with PostgreSQL data from Goose, start by creating and configuring a PostgreSQL connection in Connect AI.
- Log into Connect AI, click Sources, and then click Add Connection
- Select PostgreSQL from the Add Connection panel
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Enter the necessary authentication properties to connect to PostgreSQL.
To connect to PostgreSQL, set the Server, Port (the default port is 5432), and Database connection properties and set the User and Password you wish to use to authenticate to the server. If the Database property is not specified, the data provider connects to the user's default database.
SSH Connectivity for PostgreSQL
You can use SSH (Secure Shell) to authenticate with PostgreSQL, whether the instance is hosted on-premises or in supported cloud environments. SSH authentication ensures that access is encrypted (as compared to direct network connections).
SSH Connections to PostgreSQL in Password Auth Mode
To connect to PostgreSQL via SSH in Password Auth mode, set the following connection properties:
- User: PostgreSQL User name
- Password: PostgreSQL Password
- Database: PostgreSQL database name
- Server: PostgreSQL Server name
- Port: PostgreSQL port number like 3306
- UserSSH: "true"
- SSHAuthMode: "Password"
- SSHPort: SSH Port number
- SSHServer: SSH Server name
- SSHUser: SSH User name
- SSHPassword: SSH Password
SSH Connections to PostgreSQL in Public Key Auth Mode
To connect to PostgreSQL via SSH in Password Auth mode, set the following connection properties:
- User: PostgreSQL User name
- Password: PostgreSQL Password
- Database: PostgreSQL database name
- Server: PostgreSQL Server name
- Port: PostgreSQL port number like 3306
- UserSSH: "true"
- SSHAuthMode: "Public_Key"
- SSHPort: SSH Port number
- SSHServer: SSH Server name
- SSHUser: SSH User name
- SSHClientCret: the path for the public key certificate file
- 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 PostgreSQL connection configured and a PAT generated, Goose can now connect to PostgreSQL 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 PostgreSQL data through Connect AI.
Step 3: Query live PostgreSQL data from Goose
With the integration complete, use the Goose chat to interact with live PostgreSQL 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 PostgreSQL
- Query the top 5 records from a table in PostgreSQL data
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Goose calls the Connect AI MCP Server and returns live results from PostgreSQL data
At this point, your Goose agent communicates with the Connect AI MCP Server and retrieves live PostgreSQL data through remote MCP tools directly from the chat.
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