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 Google ADK 6 tools — connect in under 2 minutes

Name: Starburst
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 6 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Starburst as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

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

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="starburst_agent",
    instruction=(
        "You help users interact with Starburst "
        "using 6 available tools."
    ),
    tools=[mcp_tools],
)

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.

Google ADK natively supports Starburst as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 6 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

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 Google ADK 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 Google ADK via MCP

Follow these steps to integrate the Starburst MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 6 tools from Starburst via MCP

Why Use Google ADK with the Starburst MCP Server

Google ADK provides unique advantages when paired with Starburst through the Model Context Protocol.

Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Starburst

Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

Seamless integration with Google Cloud services means you can combine Starburst tools with BigQuery, Vertex AI, and Cloud Functions

Starburst + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Starburst MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Starburst and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Starburst tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Starburst regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Starburst

Starburst MCP Tools for Google ADK (6)

These 6 tools become available when you connect Starburst to Google ADK 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 Google ADK

Ready-to-use prompts you can give your Google ADK 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 Google ADK

Common issues when connecting Starburst to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Starburst + Google ADK FAQ

Common questions about integrating Starburst MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.