How to Use the StarRocks MCP in CrewAI

Q: Can I use CrewAI agents to check resource availability in StarRocks?

Yes, you can assign an 'Operations Agent' to run getstorageusage and listnodes. This lets your team automatically audit cluster capacity before launching a major job.

Q: What is the best way to list all available schemas with StarRocks and CrewAI?

Have one agent run listdatabases, then have another iterate using listtables for each returned database. This two-step process ensures complete coverage of all data assets.

Q: If I need schema details for a table in StarRocks and CrewAI, which tool should I use?

Use gettableschema. The 'Data Architect Agent' can call this to retrieve metadata—column names and data types—allowing the subsequent analysis agent to write precise queries.

Coordinate StarRocks data analysis with specialized agents using CrewAI's framework.

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Setup StarRocks with CrewAI

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Orchestrate Full Database Inventory

You can assign different tasks to different 'agents.' Agent A uses `list_databases` to get the top level view. Then, Agent B takes those results and calls `list_tables` for each one. This structured approach ensures no database is missed. The shared memory within CrewAI makes this possible; the output of the first agent becomes the input context for the second.

Deeply Analyze Data Structures

To get granular details, you can assign a 'Schema Agent' to use `get_table_schema`. This tool pulls column definitions and data types. You then pass this schema information to an 'Analysis Agent' for validation. This specialized collaboration pattern allows your operations to validate complex datasets before writing any queries.

Audit Resources and Views

Need a full resource audit? One agent can check system components using `get_cluster_info`, while another agent uses `list_views` and `list_mvs`. They collaborate to build a single, comprehensive inventory report. This specialized separation of tasks makes the overall operation more reliable than running everything through one monolithic script.

Setup guide

Set up StarRocks MCP in CrewAI

Prerequisites

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

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke StarRocks tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="StarRocks Analyst",
    goal="Access and analyze StarRocks data via MCP.",
    backstory="Expert analyst with direct StarRocks access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent StarRocks transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="StarRocks Analyst",
        goal="Access and analyze StarRocks data via MCP.",
        backstory="Expert analyst with direct StarRocks access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent StarRocks transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by StarRocks. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about StarRocks MCP in CrewAI

CrewAI handles tool exposure by letting you pass a filtered list of MCP servers and their available tools. It maps these functions to specialized agent roles, ensuring the right agent uses the right function.

Yes, you can assign an 'Operations Agent' to run `get_storage_usage` and `list_nodes`. This lets your team automatically audit cluster capacity before launching a major job.

Have one agent run `list_databases`, then have another iterate using `list_tables` for each returned database. This two-step process ensures complete coverage of all data assets.

The underlying Vinkius platform handles authentication via a single endpoint token, so your agents don't need to worry about managing multiple credentials for the StarRocks cluster.

Use `get_table_schema`. The 'Data Architect Agent' can call this to retrieve metadata—column names and data types—allowing the subsequent analysis agent to write precise queries.

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