Cube.dev MCP Server for AutoGenGive AutoGen instant access to 15 tools to Check Live, Check Ready, Convert Query, and more

Name: Cube.dev
Price: 29 USD
Availability: InStock
Rating: 0.2 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Cube.dev as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.

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The Cube.dev MCP Server for AutoGen is a standout in the Brain Trust category — giving your AI agent 15 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

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python

import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with McpWorkbench(
        server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
        transport="streamable_http",
    ) as workbench:
        tools = await workbench.list_tools()
        agent = AssistantAgent(
            name="cubedev_agent",
            tools=tools,
            system_message=(
                "You help users with Cube.dev. "
                "15 tools available."
            ),
        )
        print(f"Agent ready with {len(tools)} tools")

asyncio.run(main())

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About Cube.dev MCP Server

Connect your Cube.dev instance to any AI agent to bridge the gap between natural language and your data warehouse. This server allows your agent to interact with Cube's semantic layer, ensuring consistent metrics and high-performance data retrieval.

AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Cube.dev tools. Connect 15 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.

What you can do

Data Querying — Execute complex REST API queries using load_query to fetch aggregated data with measures, dimensions, and filters.
SQL Inspection — Use get_sql and execute_cube_sql to debug or run raw queries against the SQL API for deep data investigation.
Metadata Exploration — Retrieve cube definitions, views, and segments via get_meta to understand your data model without leaving the chat.
Performance Management — Trigger and monitor background pre-aggregation builds with trigger_pre_aggregation_job to ensure your dashboards stay fast.
Cloud Management — List deployments and environments if using Cube Cloud to manage your infrastructure context.

trigger

Trigger pre aggregation job on Cube.dev

Trigger a pre-aggregation build job

Connect Cube.dev to AutoGen via MCP

Follow these steps to wire Cube.dev into AutoGen. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install AutoGen

Run pip install "autogen-ext[mcp]"

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Integrate into workflow

Use the agent in your AutoGen multi-agent orchestration

Explore tools

The workbench discovers 15 tools from Cube.dev automatically

Why Use AutoGen with the Cube.dev MCP Server

AutoGen provides unique advantages when paired with Cube.dev through the Model Context Protocol.

Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Cube.dev tools to solve complex tasks

Role-based architecture lets you assign Cube.dev tool access to specific agents. a data analyst queries while a reviewer validates

Human-in-the-loop support: agents can pause for human approval before executing sensitive Cube.dev tool calls

Code execution sandbox: AutoGen agents can write and run code that processes Cube.dev tool responses in an isolated environment

Cube.dev + AutoGen Use Cases

Practical scenarios where AutoGen combined with the Cube.dev MCP Server delivers measurable value.

Collaborative analysis: one agent queries Cube.dev while another validates results and a third generates the final report

Automated review pipelines: a researcher agent fetches data from Cube.dev, a critic agent evaluates quality, and a writer produces the output

Interactive planning: agents negotiate task allocation using Cube.dev data to make informed decisions about resource distribution

Code generation with live data: an AutoGen coder agent writes scripts that process Cube.dev responses in a sandboxed execution environment

Example Prompts for Cube.dev in AutoGen

Ready-to-use prompts you can give your AutoGen agent to start working with Cube.dev immediately.

"Show me the metadata for all available cubes and views."

"Run a query to get the total count of orders grouped by status for the last 30 days."

"Trigger a pre-aggregation build for the 'Sales' cube."

Troubleshooting Cube.dev MCP Server with AutoGen

Common issues when connecting Cube.dev to AutoGen through Vinkius, and how to resolve them.

McpWorkbench not found

Install: pip install "autogen-ext[mcp]"

Cube.dev + AutoGen FAQ

Common questions about integrating Cube.dev MCP Server with AutoGen.

How does AutoGen connect to MCP servers?

Create an MCP tool adapter and assign it to one or more agents in the group chat. AutoGen agents can then call Cube.dev tools during their conversation turns.

Can different agents have different MCP tool access?

Yes. AutoGen's role-based architecture lets you assign specific MCP tools to specific agents, so a querying agent has different capabilities than a reviewing agent.

Does AutoGen support human approval for tool calls?

Yes. Configure human-in-the-loop mode so agents pause and request approval before executing sensitive MCP tool calls.

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