How to Use the Highlight (Session Replay & UX) MCP in OpenAI Agents SDK

Send OTLP data straight to Highlight (Session Replay & UX) from your OpenAI Agents SDK production pipeline.

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Connect Highlight (Session Replay & UX) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Highlight (Session Replay & UX) 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 Highlight (Session Replay & UX) with OpenAI Agents SDK

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Automated log ingestion with OpenAI Agents SDK

Your agent pushes logs directly into your dashboard using `ingest_otlp_logs`. It attaches the project ID automatically so your session data stays organized. This keeps your observability tight. No more context switching when your agent hits a snag during runtime.

Trace your agent's execution path

Use `ingest_otlp_traces` to map out exactly what your agent is doing. Every span gets captured so you can see the full request flow. It works inside your existing async context manager. You get visibility into every decision your agent makes without writing custom telemetry code.

Capture raw events instantly

Sometimes you just need to dump a string and move on. `ingest_raw_log` handles unstructured data for those quick-and-dirty debugging sessions. It's built for speed. If you're building a production agent, you'll appreciate how it logs failures without bloating your main logic.

Setup guide

Set up Highlight (Session Replay & UX) 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 Highlight (Session Replay & UX) tools at runtime.
3

Create your Agent

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

Run the agent

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

You instantiate the server with the Vinkius endpoint and pass it to your agent constructor. The SDK discovers the tools automatically, letting you call them within your standard async flow.

Absolutely. By setting cacheToolsList to true, you ensure your agent calls are performant. The server handles the connection while your agent focuses on the task at hand.

Yes. Since the tools are exposed to the agent framework, your defined guardrails validate the inputs before any log or trace data hits the Highlight API.

The server catches the failure and logs it through your chosen tool. You can then review the session replay to see exactly what input triggered the error.

The server transmits only the observability data you explicitly send via the tools. It touches no other parts of your agent's memory or internal state.

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