Can the AI run write or drop queries?

That depends on your token's permissions. The `execute_query` tool passes any SQL to Starburst. To prevent mutations, provision a read-only token via your Starburst security settings.

How do I handle queries that return thousands of rows?

Always add a `LIMIT` clause in your SQL. Large result sets can exceed the AI's context window. Instruct the agent to use `LIMIT 10` or `LIMIT 50` to keep responses manageable.

What credentials do I need?

Two values: `STARBURST_HOST` (your cluster URL, e.g., `https://mycluster.trino.galaxy.starburst.io`) and `STARBURST_TOKEN` (a service account token from your Starburst admin settings).

Starburst MCP Server for OpenAI Agents SDK 6 tools — connect in under 2 minutes

Name: Starburst
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 6 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Starburst through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Starburst Assistant",
            instructions=(
                "You help users interact with Starburst. "
                "You have access to 6 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Starburst"
        )
        print(result.final_output)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Starburst MCP Server

Integrate the powerful federated data analytics capabilities of Starburst directly into your conversational AI workflows. Empower your data engineering and analytics teams to query extensive data lakes, manage organizational roles, and explore detailed schemas without needing to explicitly switch between database clients. Securely map your AI assistant to your Starburst host, enabling natural language orchestration of complex Trino-based data products to accelerate data discovery and governance across your entire enterprise architecture.

The OpenAI Agents SDK auto-discovers all 6 tools from Starburst through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Starburst, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.

What you can do

Federated Query Execution — Pass complex SQL statements programmatically against your connected data sources utilizing execute_query, receiving structured analytic returns directly.
Schema & Catalog Discovery — Actively map your data landscape by inspecting linked databases invoking list_catalogs, and drill down into specific table hierarchies using list_schemas.
Data Product Management — Manage and retrieve existing analytical data products across the Starburst network systematically validating data definitions using list_data_products.
Governance & Role Administration — Inspect access control limitations securely by navigating role assignments formally deploying requests through list_roles and evaluating privilege thresholds.

The Starburst MCP Server exposes 6 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Starburst to OpenAI Agents SDK via MCP

Follow these steps to integrate the Starburst MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 6 tools from Starburst

Why Use OpenAI Agents SDK with the Starburst MCP Server

OpenAI Agents SDK provides unique advantages when paired with Starburst through the Model Context Protocol.

Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Starburst + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Starburst MCP Server delivers measurable value.

Automated workflows: build agents that query Starburst, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents — one queries Starburst, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Starburst tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Starburst to resolve tickets, look up records, and update statuses without human intervention

Starburst MCP Tools for OpenAI Agents SDK (6)

These 6 tools become available when you connect Starburst to OpenAI Agents SDK via MCP:

get_query_details

Retrieves details for a specific SQL query

list_catalogs

g., S3, Snowflake, Iceberg) are connected. Lists all data catalogs available in Starburst Galaxy

list_data_products

Lists all published data products

list_domains

Lists data product domains

list_queries

Lists recent SQL queries executed in the cluster

list_roles

Lists all security roles in the organization

Example Prompts for Starburst in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Starburst immediately.

"List all active operational catalogs across the current data lake instance, and fetch the underlying schematics of any source containing the designation 'finance' in its structure."

"Execute a query to retrieve the top 10 rows from the 'customer_analytics' table located in our 'production_hive' catalog."

"List all registered data products across the Starburst network and check current role assignments to ensure proper access."

Troubleshooting Starburst MCP Server with OpenAI Agents SDK

Common issues when connecting Starburst to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Starburst + OpenAI Agents SDK FAQ

Common questions about integrating Starburst MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.