How to Use the OceanBase MCP in CrewAI

Q: How do I assign OceanBase MCP Server tools to a specific CrewAI agent?

Pass your Vinkius server URL directly to the agent's mcps array parameter during initialization. This exposes tools like listinstances to that specific agent's toolbox while keeping other agents focused on their own roles.

Q: Can a CrewAI agent team manage multiple OceanBase clusters at once?

Yes. Your monitoring agent can use listclusters to gather telemetry across all zones, then delegate specific optimization tasks to worker agents using getresourcestats.

Deploy specialized CrewAI agent teams to monitor, analyze, and optimize your OceanBase databases autonomously.

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Connect OceanBase MCP to CrewAI

Create your Vinkius account to connect OceanBase to CrewAI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup OceanBase with CrewAI

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Multi-Agent Database Operations

`list_clusters` serves as the initial discovery tool for your database administrator agent running over MCP. This agent scans your entire footprint, identifying which clusters require immediate performance reviews. Once identified, a separate analyst agent uses `get_cluster_details` to run deep diagnostics on the target node. The agents share this context in their common memory pool to coordinate remediation steps.

Multi-Agent Tenant Optimization with CrewAI

`list_tenants` allows your resource manager agent to audit tenant distributions across your active instances. It works in tandem with a cost-control agent to spot underutilized allocations. By analyzing the data from `get_tenant_details`, the crew can flag tenants that are hogging memory or running out of storage. They compile these findings into an actionable report without you lifting a finger.

Automated Account Workspace Audits

`get_workspaces` provides your governance crew with a complete map of your active database projects via MCP Server tools. The security agent uses this list to verify that only authorized teams have access. By cross-referencing this map with `list_databases`, the agents pinpoint unmapped schemas that might represent security holes. This background audit runs continuously, keeping your compliance posture clean.

Setup guide

Set up OceanBase 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 OceanBase tools as needed.

crew.py

from crewai import Agent, Task, Crew

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

task = Task(
    description="List recent OceanBase 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="OceanBase Analyst",
        goal="Access and analyze OceanBase data via MCP.",
        backstory="Expert analyst with direct OceanBase access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent OceanBase 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 OceanBase. 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 OceanBase MCP in CrewAI

Pass your Vinkius server URL directly to the agent's `mcps` array parameter during initialization. This exposes tools like `list_instances` to that specific agent's toolbox while keeping other agents focused on their own roles.

Yes. Your monitoring agent can use `list_clusters` to gather telemetry across all zones, then delegate specific optimization tasks to worker agents using `get_resource_stats`.

They use CrewAI's shared memory system. When one agent runs `get_tenant_details`, the resulting JSON payload is indexed and made available to all other agents in the crew for collaborative decision-making.

No, CrewAI handles the underlying transport automatically. Whether your server runs on stdio or SSE, the framework translates the tool schemas so your agents can query the database metrics directly.

The agents only interact with the high-level metadata exposed by tools like `get_instance_details` through the secure Vinkius gateway. No raw database logs or master passwords are ever exposed to the model context.

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