How to Use the Dynatrace (APM and Observability) MCP in OpenAI Agents SDK

Q: What python packages do I need to start?

Install openai-agents via pip to get the core framework. Then, set up the streamable HTTP transport pointing to your Vinkius endpoint. It takes fewer than ten lines of code to get a working agent.

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Connect Dynatrace (APM and Observability) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Dynatrace (APM and Observability) 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 Dynatrace (APM and Observability) with OpenAI Agents SDK

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Automate incident triage and resolution

The `list_problems` tool lets your agent pull open alerts directly into your OpenAI execution environment. From there, the agent can inspect the root cause using `get_problem` to evaluate affected nodes. This MCP setup prevents alert fatigue without exposing your production environment to unvalidated write actions. If an alert is a known false positive, the agent uses `close_problem` to clear the log.

Real-time infrastructure health checks

The `query_metrics` tool gives your agent direct access to raw performance telemetry. It pulls raw numbers on memory, CPU, or network throughput without requiring you to open the Dynatrace console. You can program a specialized agent to compare these metrics against baseline thresholds. If anomalies crop up, the agent pushes custom data points using `ingest_metrics` to keep your dashboards accurate.

Run synthetic testing on demand

The `trigger_synthetic_batch` tool executes your pre-configured synthetic monitors instantly during deployment pipelines. This ensures you catch breaking changes before your actual users do. Your agent tracks the execution state with `list_synthetic_executions` to verify performance. If a test fails, the agent stops the deployment and logs a custom event via `ingest_events`.

Setup guide

Set up Dynatrace (APM and Observability) 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 Dynatrace (APM and Observability) tools at runtime.
3

Create your Agent

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

Run the agent

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

The SDK automatically queries the running MCP server to map all 37 tools at startup. You do not need to write manual JSON schemas or register functions. Just pass the server connection to your agent configuration, and it handles the rest.

Yes, you can enforce strict guardrails inside your Python code to block specific tools. For instance, you can allow read tools like `list_problems` while blocking destructive ones like `delete_dashboard`. This keeps your production environment safe from unintended agent actions.

Every tool execution appears directly inside your OpenAI developer dashboard. You can inspect the exact arguments passed to tools like `query_metrics` and see the raw JSON response returned by the server. This makes debugging agent decisions incredibly straightforward.

Install `openai-agents` via pip to get the core framework. Then, set up the streamable HTTP transport pointing to your Vinkius endpoint. It takes fewer than ten lines of code to get a working agent.

Your raw performance metrics and problem details never leave the secure V8 sandbox. Vinkius executes the MCP Server in an isolated, ephemeral container that destroys itself after the session ends. Your Dynatrace API tokens are encrypted at rest and injected only at execution time.

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