How do I find my StarRocks FE Host and Port?

The FE Host is the IP address or domain of your StarRocks Frontend node. The default HTTP port is 8030. You can verify these in your deployment configuration or by contacting your administrator.

Can I execute DELETE or UPDATE queries through this server?

Yes. Use the `execute_query` tool. As long as your authenticated user has the necessary permissions in StarRocks, you can execute any valid SQL statement, including DDL and DML operations.

Is it possible to monitor cluster health through the agent?

Yes! Use the `get_cluster_info` and `list_nodes` tools to retrieve real-time status for all Frontend and Backend nodes, helping you identify offline or overloaded nodes instantly.

StarRocks MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: StarRocks
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect StarRocks through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

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 pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

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

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to StarRocks "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in StarRocks?"
    )
    print(result.data)

asyncio.run(main())

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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 StarRocks MCP Server

Empower your AI agent to orchestrate your high-performance OLAP infrastructure with StarRocks, the leading distributed analytical database. By connecting StarRocks to your agent, you transform complex cluster auditing, schema management, and data querying into a natural conversation. Your agent can instantly list databases, retrieve table schemas, monitor backend nodes, and even execute complex SQL queries without you ever needing to open a SQL terminal or the StarRocks Manager. Whether you are conducting a data audit or monitoring real-time ingestion jobs, your agent acts as a real-time data reliability assistant, keeping your analytical platform accurate and your insights moving.

Pydantic AI validates every StarRocks tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Database Orchestration — List all databases and retrieve detailed table schemas and structures.
Analytical Querying — Execute arbitrary SQL queries directly through the agent to retrieve real-time insights.
Cluster Monitoring — Browse status and metadata for Frontend (FE) and Backend (BE) nodes to audit health.
Ingestion Control — Monitor data load jobs and historical ingestion performance for your analytical pipelines.
Storage Insights — Retrieve disk usage and data size statistics across the entire distributed cluster.

The StarRocks MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI 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 StarRocks to Pydantic AI via MCP

Follow these steps to integrate the StarRocks MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from StarRocks with type-safe schemas

Why Use Pydantic AI with the StarRocks MCP Server

Pydantic AI provides unique advantages when paired with StarRocks through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your StarRocks integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your StarRocks connection logic from agent behavior for testable, maintainable code

StarRocks + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the StarRocks MCP Server delivers measurable value.

Type-safe data pipelines: query StarRocks with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple StarRocks tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query StarRocks and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock StarRocks responses and write comprehensive agent tests

StarRocks MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect StarRocks to Pydantic AI via MCP:

execute_query

Execute arbitrary SQL query

get_cluster_info

Get frontend nodes info

get_storage_usage

Get data storage statistics

get_table_schema

Get table structure

list_databases

List all databases

list_jobs

List data load jobs

list_mvs

List materialized views

list_nodes

List backend nodes

list_tables

List tables in a database

list_views

List database views

Example Prompts for StarRocks in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with StarRocks immediately.

"List all databases in my StarRocks cluster."

"Show me the average order value from the 'sales' table."

"Check for any offline backend nodes."

Troubleshooting StarRocks MCP Server with Pydantic AI

Common issues when connecting StarRocks to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

StarRocks + Pydantic AI FAQ

Common questions about integrating StarRocks MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your StarRocks MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.