Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Snowflake Cube Server show me sales data for the last quarter"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Server for Interacting with Cube Semantic Layers
context://data_descriptionContains a description of the data available in the Cube deployment. This is an application controlled version of the describe_data tool.
data://{data_id}Contains the data returned by a read_data call in JSON format. This resource is meant for MCP clients that wish to format or otherwise process the output of tool calls. See read_data for more.
Related MCP server: iceberg-mcp-server
read_dataAccepts a query to the Cube REST API and returns the data in YAML along with a unique identifier for the data returned. This identifier can be used to a retrieve a JSON representation of the data from the resource data://{data_id}. See data://{data_id} for more.
describe_dataDescribes the data available in the Cube deployment. This is an agentic version of the context://data_description resource.
This server cannot be installed
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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MCP server for interacting with the Supabase platform
MCP server providing access to the Scorecard API to evaluate and optimize LLM systems.
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/isaacwasserman/mcp_cube_server'
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