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The Cube D3 MCP (Model Context Protocol) Server provides seamless integration with AI assistants like Claude Desktop and Cursor, enabling direct chat functionality with Cube’s AI agent for analytics and data exploration.

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What is MCP?

Model Context Protocol (MCP) is an open standard that enables AI assistants to securely connect to external data sources and tools. The Cube MCP Server acts as a bridge between your AI assistant and Cube’s analytics platform, allowing you to ask data questions directly from your coding environment.

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Tools Available

  • chat: Interactive chat with Cube AI agent for analytics and data exploration with streaming real-time responses

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Installation & Setup

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Prerequisites

Before setting up the MCP server, ensure you have:
  • Admin privileges in your Cube D3 instance
  • An active Cube D3 tenant
  • Claude Desktop or Cursor installed

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1. Obtain Required Credentials

You’ll need four key pieces of information:

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CUBE_API_KEY

  • Navigate to Admin → API Keys to create and manage API keys
  • Create a new API key for your Cube organization
  • For detailed instructions, see our API Keys documentation

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CUBE_TENANT_NAME

  • Your tenant name from the URL (e.g., ‘acme’ in https://acme.cubecloud.dev)

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CUBE_AGENT_ID

  • Navigate to Admin → Agent → Click on Agent to find the Agent ID

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USER_ID

  • Can be the email address of a registered user in your Cube D3 instance
  • Or any custom unique identifier for unregistered users
  • This helps identify and personalize responses from the AI agent

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Configuration

Add the following configuration to your Claude Desktop or Cursor MCP settings: 
{
  "mcpServers": {
    "cube-mcp-server": {
      "command": "npx",
      "args": ["@cube-dev/mcp-server"],
      "env": {
        "CUBE_API_KEY": "your_api_key_here",
        "CUBE_TENANT_NAME": "your_tenant_name",
        "CUBE_AGENT_ID": "your_agent_id",
        "USER_ID": "user@example.com"
      }
    }
  }
}

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Usage Examples

Once configured, you can interact with Cube’s AI agent directly from your AI assistant: Ask natural language questions about your data:
  • “Show me revenue trends for the last 6 months”
  • “What are our top-performing products this quarter?”
  • “How does customer acquisition compare year-over-year?”
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