How to Use the StarRocks MCP in OpenAI Agents SDK

Q: What data does the OpenAI Agents SDK retrieve when listing nodes for StarRocks?

The listnodes tool returns detailed information about every backend node in your cluster. It helps you map out physical resource distribution across different machines.

Q: If I use the OpenAI Agents SDK to check storage usage on StarRocks, what metrics do I get?

The getstorageusage tool provides clear statistics on how much data is stored. You'll see precise metrics broken down by segment or database.

Q: Can the OpenAI Agents SDK list materialized views for StarRocks?

Yep, you can. The listmvs tool lets your agent get a full rundown of all defined materialized views in the StarRocks environment.

Connect your AI agents to StarRocks and get sub-second data answers using the OpenAI Agents SDK.

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Connect StarRocks MCP to OpenAI Agents SDK

Create your Vinkius account to connect StarRocks to OpenAI Agents SDK — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup StarRocks with OpenAI Agents SDK

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Run complex queries instantly.

You use `execute_query` to run arbitrary SQL against StarRocks. The agent handles formatting and sends the query, returning results directly. The system supports complex joins and aggregations, giving you immediate data insights without manual query building.

Check database structure easily.

Need to know what's in a table? Call `get_table_schema`. It returns the exact column names and their data types right away. This lets your agent confirm if the source data is structured the way it expects, saving time on debugging.

Monitor cluster resources.

Figure out where your data lives by running `list_databases`. It provides a quick inventory of every available database in StarRocks. Want to see what tables exist? Just call `list_tables` and you get an immediate list of all schemas within a given database.

Setup guide

Set up StarRocks MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all StarRocks tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives StarRocks tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate StarRocks tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="StarRocks Agent",
            instructions="You have access to StarRocks tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about StarRocks MCP in OpenAI Agents SDK

The agent validates actions using built-in guardrails before sending anything to StarRocks. This means it checks syntax and context, so you don't send invalid SQL that fails mid-run.

The `list_nodes` tool returns detailed information about every backend node in your cluster. It helps you map out physical resource distribution across different machines.

The `get_storage_usage` tool provides clear statistics on how much data is stored. You'll see precise metrics broken down by segment or database.

Yep, you can. The `list_mvs` tool lets your agent get a full rundown of all defined materialized views in the StarRocks environment.

The server touches database schema information, specifically column names and data types. Your agent only acts on the results returned by the tool calls; it doesn't export raw data unless explicitly instructed.

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