How to Use the Determ MCP in OpenAI Agents SDK

Q: Can the OpenAI Agents SDK filter Determ mentions by keyword?

Yes. Your agent calls the searchmentionsbykeyword tool directly. The SDK automatically validates the keyword arguments before sending the request to the MCP server.

Q: How does the OpenAI Agents SDK handle Determ API limits?

The agent runs getaccountmetadata to check your current subscription limits. You can write custom guardrails that stop the agent from exceeding your monthly mention quota.

Build production-ready media monitoring agents with OpenAI Agents SDK and Determ.

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Connect Determ MCP to OpenAI Agents SDK

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

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Autonomous brand tracking with this MCP Server

Setting up a media tracking agent requires the `list_monitoring_queries` tool to reliably access your live queries. By connecting this MCP Server, your OpenAI agent automatically discovers the required endpoints at startup. You configure the guardrails, and the agent safely polls for new topics without needing custom API wrappers. Once the agent knows what to look for, it runs `list_media_mentions` to pull in the raw data. The OpenAI dashboard tracks every single tool call. If the agent starts hitting rate limits, the built-in safety constraints pause execution before your Determ account gets locked out.

Safe sentiment analysis at scale

Raw mentions require the `get_query_sentiment_summary` tool to classify brand perception across thousands of articles. Because you are using the OpenAI Agents SDK, you can route negative sentiment spikes directly to a specialized crisis-response agent. The handoff happens natively. High-impact news demands immediate attention. The agent triggers `list_recent_high_reach_mentions` to filter out low-tier blogs and focus on major publications. This prevents your downstream workflows from choking on irrelevant noise.

Traceable report generation

Production systems use the `list_analytics_reports` tool to generate auditable outputs from your existing Determ dashboards. The agent reads the available metrics and formats them into a daily briefing for your PR team. You get consistent reporting every morning. If a specific article looks suspicious, the agent executes `get_mention_details` to pull the full text and technical metadata. Every step of this investigation gets logged in your OpenAI traces. You know exactly why the agent flagged that specific piece of content.

Setup guide

Set up Determ 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 Determ tools at runtime.
3

Create your Agent

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

Run the agent

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

Install the openai-agents package via pip. Initialize this MCP Server using the MCPServerStreamableHttp class with your Vinkius endpoint URL, then pass it to your Agent constructor. Set cacheToolsList to true to speed up initialization.

Yes. Your agent calls the search_mentions_by_keyword tool directly. The SDK automatically validates the keyword arguments before sending the request to the MCP server.

You can share the server instance across your entire OpenAI agent network. A tracking agent pulls the data, and a reporting agent formats it. Handoffs happen natively within the framework.

The agent runs get_account_metadata to check your current subscription limits. You can write custom guardrails that stop the agent from exceeding your monthly mention quota.

This integration reads your media mentions, author metadata, and sentiment scores. Vinkius runs the server in an ephemeral V8 Isolate sandbox, meaning your raw PR data and API tokens disappear the second the session ends.

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