How to Use the DISQO MCP in OpenAI Agents SDK
Connect your OpenAI Agents SDK to DISQO. Pull behavioral metrics and manage research projects directly within your agent workflow.
Works with every AI agent you already use
…and any MCP-compatible client
Connect DISQO MCP to OpenAI Agents SDK
Create your Vinkius account to connect DISQO 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.
Real-time project tracking for OpenAI Agents SDK
Your agent monitors active research pipelines without leaving its environment. It uses `list_running_research_projects` to identify which consumer studies are currently collecting data. Once a project is identified, the agent calls `get_project_details` to verify settings. This ensures your agent always operates on current project configurations.
Automated behavioral audits with MCP Server
Stop manual data checks. Your agent executes `quick_behavioral_audit` to pull high-level summaries of active consumer metrics directly into its decision loop. You can then use `list_behavioral_metrics` to drill down into specific data points. This provides your agent with the necessary context to assess consumer behavior instantly.
Audience segment analysis for your agent
Identify the right research targets without human intervention. Your agent employs `list_largest_research_panels` to find segments with the most available panelists for your study. It verifies these segments using `list_research_audiences` before proceeding. This keeps your research focused on high-density demographics.
Set up DISQO MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all DISQO tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives DISQO tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate DISQO tools and returns structured results. Copy the full example on the right to get started.
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="DISQO Agent",
instructions="You have access to DISQO tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main()) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by DISQO. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
Why Choose Vinkius
Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.
Real-time monitoring
Live
visibility into every interaction
Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.
Single dashboard
One
place for every integration
Every tool your AI connects to, managed from a single screen. One account, complete control.
Common questions about DISQO MCP in OpenAI Agents SDK
Use it with your favorite AI tools
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