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 LangChain 10 tools — connect in under 2 minutes

Name: StarRocks
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect StarRocks through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "starrocks": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using StarRocks, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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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 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.

LangChain's ecosystem of 500+ components combines seamlessly with StarRocks through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the StarRocks MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from StarRocks via MCP

Why Use LangChain with the StarRocks MCP Server

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

The largest ecosystem of integrations, chains, and agents. combine StarRocks MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across StarRocks queries for multi-turn workflows

StarRocks + LangChain Use Cases

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

RAG with live data: combine StarRocks tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query StarRocks, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain StarRocks tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every StarRocks tool call, measure latency, and optimize your agent's performance

StarRocks MCP Tools for LangChain (10)

These 10 tools become available when you connect StarRocks to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

StarRocks + LangChain FAQ

Common questions about integrating StarRocks MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.