Cube MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| CUBE_API_KEY | No | Navigate to Admin → API Keys to obtain your API key. | |
| EXTERNAL_USER_ID | No | A unique identifier for external/third-party users (e.g., "user-123", "customer@external.com"). Use this when you need to provide custom user attributes, groups, or row-level security settings. | |
| INTERNAL_USER_ID | No | Email address of an existing Cube user. Use this for internal team members who already have Cube accounts. The user's existing permissions and settings will be used. | |
| CUBE_CHAT_API_URL | No | Copy the complete Chat API URL from Admin → Agents → Click on Agent → Chat API URL field. This is the full endpoint URL for your agent. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
| resources | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| chatB | Chat with Cube AI agent for analytics and data exploration. Returns streaming response with AI insights, tool calls, and data visualizations. Supports both external users (with custom attributes) and internal Cube users (with existing permissions). |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| Server Information | Basic information about this MCP server |
| Example Configuration | Example configuration data |
TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'chat' has a clearly distinct and singular purpose, focused on interacting with an AI agent for analytics and data exploration.
A single tool inherently exhibits perfect naming consistency, as there are no other tools to compare against. The name 'chat' is straightforward and follows a simple verb pattern, with no deviations or mixed conventions present.
A single tool is too few for a server named 'Cube MCP Server', which suggests a broader analytics and data exploration domain. While the tool is versatile, the lack of complementary tools (e.g., for data querying, visualization management, or user management) makes the surface feel thin and incomplete for the implied scope.
The tool set is severely incomplete for analytics and data exploration. Although 'chat' provides AI-driven insights, there are obvious gaps such as direct data retrieval, visualization creation, user permission management, or data manipulation tools. This will likely cause agent failures when attempting comprehensive workflows beyond conversational interactions.