How to Use the OceanBase MCP in AutoGen

Q: How do I register OceanBase tools with an AutoGen assistant agent?

Use the mcpservertools adapter from autogen-ext to fetch the tools from the MCP endpoint. Pass the resulting tool list to your AssistantAgent constructor to give it access to listclusters and other commands.

Q: Can AutoGen agents monitor multiple OceanBase instances simultaneously?

Yes, by executing listinstances to map the deployment and then running parallel queries with getinstancedetails. The AutoGen framework coordinates these calls across different specialized agents.

Build multi-agent consensus networks in AutoGen to coordinate and validate OceanBase database operations.

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Create your Vinkius account to connect OceanBase to AutoGen 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 AutoGen

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Multi-agent consensus for OceanBase tenant management

`list_tenants` allows your AutoGen database administrator agent to discover active tenants and propose resource reallocations. A separate security agent then uses `get_tenant_details` to check that the proposed changes comply with isolation policies. This multi-agent debate ensures no single agent makes unverified changes to your OceanBase cluster. The agents negotiate the optimal configuration based on real-time tenant metrics before presenting a final plan.

Collaborative cluster diagnostics in AutoGen

`get_cluster_details` provides the raw cluster topology that your AutoGen diagnostic agents analyze. One agent focuses on hardware performance while another reviews database configuration, debating the root cause of any anomalies. By dividing the analysis, AutoGen agents identify complex distributed database issues faster. They cross-reference cluster details with instance metrics to locate bottlenecks without human intervention.

Schema validation via AutoGen MCP Server workflows

`list_databases` pulls the active database inventory for your AutoGen schema validation agent to review. The agent compares the live database list against your target migration files to detect drift. This automated review loop prevents deployment errors on your OceanBase clusters. The AutoGen agents run this check as part of your CI/CD pipeline, ensuring schemas match before any code is merged.

Setup guide

Set up OceanBase MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes OceanBase tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="OceanBase_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent OceanBase data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

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

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="OceanBase_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent OceanBase data")
    print(result.messages[-1].content)

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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 AutoGen

Use the `mcp_server_tools` adapter from `autogen-ext` to fetch the tools from the MCP endpoint. Pass the resulting tool list to your `AssistantAgent` constructor to give it access to `list_clusters` and other commands.

Agents use a conversational loop to debate the output of tools like `get_resource_stats`. A manager agent coordinates the discussion, ensuring the performance and security agents agree before executing a task.

Yes, by executing `list_instances` to map the deployment and then running parallel queries with `get_instance_details`. The AutoGen framework coordinates these calls across different specialized agents.

Yes, you can connect your AutoGen agents to the OceanBase MCP Server using the streamable HTTP transport. This ensures stable, low-latency tool execution even in complex multi-agent conversations.

The server only exposes configuration metadata, such as workspace details from `get_workspaces` and project names from `list_projects`. Vinkius runs the server in an ephemeral, zero-trust sandbox, preventing any exposure of actual table data.

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