Interact with Live Snowflake Data in Meta Muse via CData Connect AI

Muse is Meta's personal AI agent for iOS, Android, and the web, built on the Muse Spark models. It connects to remote model context protocol (MCP) servers, so you can point Muse at a governed data source and let it discover and call live data tools.

Connect Muse to CData Connect AI through its Remote MCP Server, and Muse gains governed, real-time access to live Snowflake data. You can explore data, fetch records, and interact with objects using natural language prompts, with every request running against authorized sources.

This article shows you how to configure Snowflake connectivity in Connect AI, generate a personal access token, create a custom connector to the Connect AI Remote MCP Server in Muse, and interact with live Snowflake data from Muse.

Getting Started

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Step 1: Configure Snowflake connectivity for Meta Muse

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

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select Snowflake from the Add Connection panel

3. Enter the necessary authentication properties to connect to Snowflake.

   To connect to Snowflake:

   1. Set User and Password to your Snowflake credentials and set the AuthScheme property to PASSWORD or OKTA.
   2. Set URL to the URL of the Snowflake instance (i.e.: https://myaccount.snowflakecomputing.com).
   3. Set Warehouse to the Snowflake warehouse.
   4. (Optional) Set Account to your Snowflake account if your URL does not conform to the format above.
   5. (Optional) Set Database and Schema to restrict the tables and views exposed.
   6. (Optional) If MFA is enabled on your Snowflake account (via Duo Security), set MFACode to the passcode generated by your Duo authenticator app.

   See the Getting Started guide in the CData driver documentation for more information.

   
4. Click Save & Test
5. 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 Muse. 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. Copy the token when displayed and store it securely. It will not be shown again

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

Step 2: Create a custom connector to the Connect AI MCP Server in Meta Muse

Muse has no manual "add MCP server" form. Instead, you ask Muse in plain language to build a custom connector that points at the Connect AI Remote MCP Server, a hosted, public HTTPS endpoint that speaks streamable HTTP. Muse builds the connector on its secure VM using the official MCP SDK, then discovers and calls the available Connect AI data tools.

1. Open Muse on iOS, Android, or the web and start a new chat
2. Ask Muse to build a custom connector to the Connect AI Remote MCP Server, giving it the server URL and noting that the endpoint is a hosted MCP server over streamable HTTP, for example:
   Create a custom connector to CData Connect AI. It is a hosted MCP server over streamable HTTP at https://mcp.cloud.cdata.com/mcp and it requires an Authorization header.
3. When Muse prompts for credentials, it opens a secure entry flow, separate from the chat, that saves the value in its Secure Credentials Store. Enter the Authorization header value in the format Basic your_base64_encoded_email_PAT

   Note: For the Authorization value, base64 encode email:PAT and prefix it with Basic. Enter it only in Muse's secure credential prompt, never in the chat.

4. Muse connects to the Connect AI MCP Server and lists the available data tools. Review the custom connector confirmation, then click Continue. When Muse offers to save the integration as a skill, choose yes so the connector is available in every future chat

With the custom connector saved, the Connect AI tools are available to Muse in any chat.

Step 3: Interact with live Snowflake data from Meta Muse

With the integration complete, interact with live Snowflake data directly from Muse through natural language prompts.

1. In a Muse chat, type a prompt that uses the Connect AI connector, for example:
   • Use the CData Connect AI connector to list all available connections
   • Show the available objects and fields for Snowflake
   • Fetch the top 5 records from Snowflake
2. Approve the tool call in the Sentinel dialog when prompted
3. Muse calls the Connect AI MCP Server and returns live results from Snowflake data

At this point, Muse communicates with the Connect AI MCP Server and retrieves live Snowflake data through remote MCP tools directly from your chats.

Get started with CData Connect AI

With CData Connect AI, interact with hundreds of SaaS, big data, and NoSQL sources directly from your AI agents, models, and cloud applications. To explore more download a free 14-day trial today. Our Support Team is available to help with any questions you have.