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 Pydantic AI 10 tools — connect in under 2 minutes

Name: OceanBase
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 OceanBase through 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 OceanBase "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in OceanBase?"
    )
    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 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.

Pydantic AI validates every OceanBase tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through 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

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 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 OceanBase to Pydantic AI via MCP

Follow these steps to integrate the OceanBase 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 OceanBase with type-safe schemas

Why Use Pydantic AI with the OceanBase MCP Server

Pydantic AI provides unique advantages when paired with OceanBase 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 OceanBase integration code

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

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

OceanBase + Pydantic AI Use Cases

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

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

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

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

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

OceanBase MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect OceanBase to Pydantic AI 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 Pydantic AI

Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

OceanBase + Pydantic AI FAQ

Common questions about integrating OceanBase 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 OceanBase MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.