How do I find my OceanBase Access Key and Secret?

Log in to your OceanBase Cloud console, go to [Security] → [Access Keys], and you will find your unique Access Key ID and Secret Key there. Ensure you keep them confidential.

Can I list databases for a specific tenant through this server?

Yes. Use the `list_databases` tool with the cluster ID and tenant ID. Your agent will retrieve the full list of logical databases belonging to that specific resource pool.

Is it possible to check organization-wide resource usage?

Yes! Use the `get_resource_stats` tool to retrieve aggregate statistics across your OceanBase account, helping you monitor total CPU, memory, and storage consumption.

OceanBase MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: OceanBase
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to OceanBase through Vinkius, pass the Edge URL in the `mcps` parameter and every OceanBase tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="OceanBase Specialist",
    goal="Help users interact with OceanBase effectively",
    backstory=(
        "You are an expert at leveraging OceanBase tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in OceanBase "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

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

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* 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 OceanBase MCP Server

Empower your AI agent to orchestrate your entire database infrastructure with OceanBase, the premier enterprise distributed relational database. By connecting OceanBase to your agent, you transform complex cluster management, tenant resource allocation, and database auditing into a natural conversation. Your agent can instantly list your database clusters, retrieve detailed configuration for tenants, monitor resource usage statistics, and browse available databases without you ever needing to navigate the OceanBase Cloud console. Whether you are conducting a capacity planning review or auditing database health across a global deployment, your agent acts as a real-time database reliability assistant, keeping your data infrastructure accurate and your systems performant.

When paired with CrewAI, OceanBase becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call OceanBase tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Cluster Orchestration — List all database clusters and retrieve detailed configuration and status information.
Tenant Management — Browse logical tenants within clusters and retrieve detailed resource allocation metadata.
Database Auditing — List all databases within specific tenants to identify data assets and structures.
Resource Monitoring — Retrieve aggregate resource usage statistics to audit system performance and capacity.
Organization Insights — Browse projects, instances, and workspaces to maintain a unified view of your database ecosystem.

The OceanBase MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI 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 OceanBase to CrewAI via MCP

Follow these steps to integrate the OceanBase MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from OceanBase

Why Use CrewAI with the OceanBase MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with OceanBase through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

OceanBase + CrewAI Use Cases

Practical scenarios where CrewAI combined with the OceanBase MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries OceanBase for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries OceanBase, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain OceanBase tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries OceanBase against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

OceanBase MCP Tools for CrewAI (10)

These 10 tools become available when you connect OceanBase to CrewAI via MCP:

get_cluster_details

Get cluster details

get_instance_details

Get instance details

get_resource_stats

Get resource statistics

get_tenant_details

Get tenant details

get_workspaces

Get account workspaces

list_clusters

List OceanBase clusters

list_databases

List tenant databases

list_instances

List OB instances

list_projects

List OB projects

list_tenants

List cluster tenants

Example Prompts for OceanBase in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with OceanBase immediately.

"List all database clusters in my OceanBase account."

"Show me the resource usage statistics for the organization."

"List all databases in tenant 'tenant-8821' inside cluster 'cluster-9920'."

Troubleshooting OceanBase MCP Server with CrewAI

Common issues when connecting OceanBase to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

OceanBase + CrewAI FAQ

Common questions about integrating OceanBase MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.