How to Use the Metronome MCP in OpenAI Agents SDK

Q: How do I register the Metronome MCP Server with OpenAI Agents SDK?

Install openai-agents via pip, then initialize MCPServerStreamableHttp using your Vinkius endpoint. Pass the server instance inside the mcpservers list when constructing your agent, setting cacheToolsList=True to keep tool discovery fast.

Q: How does OpenAI Agents SDK handle tracing for Metronome event ingestion?

Every time your agent calls ingestevents, the OpenAI dashboard captures the full request and response payload. You can trace the exact flow from the raw application logs to the successful ingestion status code.

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Connect Metronome MCP to OpenAI Agents SDK

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

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Automate customer lifecycle events with OpenAI Agents SDK

The `create_customer` tool lets your agent provision new users in your billing system as soon as they sign up in your app. Your specialized provisioning agent built with OpenAI Agents SDK spins up, runs this tool, and then hands off to a contract agent that executes `create_contract` to bind them to a pricing tier. Using the native guardrails in OpenAI Agents SDK, you can intercept these tool calls to verify the customer payload before it hits your live billing system. This keeps your automated pipelines from executing empty or corrupted customer setups.

Real-time high-throughput event ingestion

The `ingest_events` tool handles up to 100,000 events per second directly from your OpenAI Agents SDK event processing loop. Your ingestion agent processes incoming raw usage logs, matches them to your schema, and pushes them straight to Metronome without missing a beat. OpenAI dashboard tracing lets you monitor every single payload sent by `ingest_events` to the MCP Server during high-volume spikes. You see exactly which agent triggered the ingestion and can debug payload mismatches right in the trace logs.

Automated invoice correction and audits

The `get_audit_logs` tool provides your OpenAI Agents SDK compliance agent with a complete trail of changes to review before running billing adjustments. If the agent detects a discrepancy, it invokes `void_invoice` and runs `regenerate_invoice` to correct the billing run. Because OpenAI Agents SDK handles state handoffs between specialized audit and billing execution agents, you don't risk race conditions. The audit agent verifies the log history first, then passes the validated context to the billing agent to execute the correction.

Setup guide

Set up Metronome 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 Metronome tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Metronome 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="Metronome Agent",
            instructions="You have access to Metronome 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 Metronome MCP in OpenAI Agents SDK

Install `openai-agents` via pip, then initialize `MCPServerStreamableHttp` using your Vinkius endpoint. Pass the server instance inside the `mcp_servers` list when constructing your agent, setting `cacheToolsList=True` to keep tool discovery fast.

Yes. You can write custom guardrail functions that intercept critical tool calls like `void_invoice` or `edit_contract` to check the arguments before they execute. This stops the agent from making destructive billing changes without your explicit approval.

Every time your agent calls `ingest_events`, the OpenAI dashboard captures the full request and response payload. You can trace the exact flow from the raw application logs to the successful ingestion status code.

Yes, you can deploy specialized agents for customer setup and invoice management. One agent uses `create_customer` while another monitors balances with `get_net_balance`, passing context back and forth as needed.

This server handles sensitive customer billing metrics, raw usage events, and contract pricing structures. All data passes through Vinkius's secure, zero-trust sandbox using ephemeral execution environments, meaning your billing keys are never exposed to the agent or stored on disk.

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