How to Use the Metaplane MCP in OpenAI Agents SDK

Q: How do I connect Metaplane to my OpenAI Agents SDK pipeline?

Install the SDK and pass MCPServerStreamableHttp pointing to your Vinkius endpoint. Your agent automatically registers MCP tools like listmonitors during startup with no manual function mapping.

Q: Can my OpenAI Agents SDK setup trigger Metaplane tests after a dbt run?

Yes. Your agent can call triggermonitorrun right after your loader finishes. It then polls getmonitorruns to verify the data is clean before starting downstream transformations.

Connect your Metaplane observability stack directly to OpenAI Agents SDK to catch and triage broken data pipelines.

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Connect Metaplane MCP to OpenAI Agents SDK

Create your Vinkius account to connect Metaplane to OpenAI Agents SDK 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 Metaplane with OpenAI Agents SDK

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Pinpoint broken tables using OpenAI Agents SDK

The `list_data_connections` tool gives your agent immediate visibility into your active databases and warehouses. When a pipeline fails, your agent queries `list_connection_schemas` to map out the exact tables and columns affected, skipping manual schema inspection entirely. This MCP Server exposes raw metadata directly to your Python workspace. Your agent uses this context to verify structure changes, preventing broken data from hitting downstream dashboards before your team even opens Slack.

Automated incident triage

The `list_incidents` tool pulls active data quality alerts directly into your agent's execution loop. Once an anomaly is detected, the agent calls `get_incident` to retrieve the blast radius, severity, and impacted downstream assets. By integrating this MCP Server, your agent acts as a first-line support engineer. It routes the incident details to the correct team or triggers remediation scripts based on the specific failure signature.

On-demand testing loops

The `trigger_monitor_run` tool executes specific data quality tests on demand when your pipelines finish loading. Your agent monitors the execution state by calling `get_monitor_runs` to ensure everything passes before clearing the pipeline for production. Instead of waiting for scheduled cron jobs, this setup runs tests exactly when your data changes. Your agent handles the polling, checks `get_monitor` details, and blocks bad deployments automatically.

Setup guide

Set up Metaplane MCP in OpenAI Agents SDK

Prerequisites

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

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Metaplane tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Metaplane tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Metaplane tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Metaplane Agent",
            instructions="You have access to Metaplane tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Metaplane MCP in OpenAI Agents SDK

Install the SDK and pass `MCPServerStreamableHttp` pointing to your Vinkius endpoint. Your agent automatically registers MCP tools like `list_monitors` during startup with no manual function mapping.

Yes. Your agent can call `trigger_monitor_run` right after your loader finishes. It then polls `get_monitor_runs` to verify the data is clean before starting downstream transformations.

The SDK uses built-in guardrails to throttle calls to endpoints like `list_data_connections`. If your agent makes too many concurrent requests, the system queues them to respect your API limits.

You control tool access through your Vinkius gateway configuration. You can expose only read-only tools like `list_incidents` while blocking write actions like `trigger_monitor_run`.

All API credentials and schema metadata are isolated within Vinkius's zero-trust sandboxes. Your OpenAI Agents SDK environment only communicates with the secure MCP endpoint, keeping database credentials hidden.

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