How to Use the AgentOps (Agent Telemetry and Monitoring) MCP in OpenAI Agents SDK

Q: How do I configure AgentOps (Agent Telemetry and Monitoring) with the OpenAI Agents SDK?

Install openai-agents via pip. Initialize MCPServerStreamableHttp with your Vinkius endpoint. Pass that instance to your Agent constructor using the mcpservers array.

Monitor your production systems by connecting AgentOps directly to your OpenAI Agents SDK deployments.

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Connect AgentOps (Agent Telemetry and Monitoring) MCP to OpenAI Agents SDK

Create your Vinkius account to connect AgentOps (Agent Telemetry and Monitoring) 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 AgentOps (Agent Telemetry and Monitoring) with OpenAI Agents SDK

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Perplexity

Inspect traces via MCP Server

Your OpenAI agents need oversight before they hit production. Using the `get_trace` tool, your agent pulls execution paths directly from AgentOps to review what happened during complex handoffs. You don't have to leave the dashboard to debug. The system fetches performance data through `get_trace_metrics` and runs it through your custom guardrails to ensure execution times stay within safety constraints.

Analyze specific spans

Granular debugging matters when a specialized agent fails mid-task. The `get_span` tool grabs the exact step where things went wrong, letting your monitoring agent flag the error automatically. This means you catch infinite loops fast. Raw span data pipes straight into your Python context, allowing your supervisor agent to halt execution before API costs spike.

Pull project-level health

Managing multiple agent deployments requires high-level visibility. Calling `get_project` returns the overall telemetry data for your active workspace without manual configuration. Your reporting agent takes this data and summarizes daily performance. It checks active sessions and error rates instantly, bypassing custom integration code entirely.

Setup guide

Set up AgentOps (Agent Telemetry and Monitoring) 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 AgentOps (Agent Telemetry and Monitoring) tools at runtime.
3

Create your Agent

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

Run the agent

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

Install `openai-agents` via pip. Initialize `MCPServerStreamableHttp` with your Vinkius endpoint. Pass that instance to your Agent constructor using the `mcp_servers` array.

Yes. The SDK maps out the tools without manual routing. Just set `cacheToolsList=True` for better startup performance.

Your agent pulls telemetry data and evaluates it against your safety constraints. If a trace duration exceeds limits, the guardrail blocks further execution.

The monitoring agent tracks the entire chain. You can query the specific spans to see exactly where one agent passed control to the next.

Vinkius runs the server in a V8 Isolate Sandbox. Your agent traces, spans, and project metrics disappear the moment the session ends.

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