How to Use the CONSENSUS MCP in OpenAI Agents SDK

Track buyer engagement within your OpenAI Agents SDK production pipeline using the CONSENSUS MCP Server.

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Connect CONSENSUS MCP to OpenAI Agents SDK

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

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Monitor demo performance in OpenAI Agents SDK

Call `list_demolytics` to pull granular engagement metrics directly into your agent's reasoning loop. You get the raw data needed to decide which prospects move forward. This keeps your agent informed on real-time buyer interest without leaving the OpenAI stack. It feeds the exact data points your decision-making agents need to qualify leads.

Manage your demo library via OpenAI Agents SDK

Use `list_demos` and `list_demoboards` to index your entire library of product walkthroughs. Your agents will know exactly what content is available to share with a prospect. This visibility ensures your agent always picks the right resource. It maps your available assets to specific user requirements automatically.

Track prospect outreach in OpenAI Agents SDK

The `list_invitations` tool lets your agent audit sent demos to identify stale conversations. It flags who hasn't opened their link yet. Your agent can then pivot its strategy based on these outreach logs. It keeps your sales pipeline moving by reacting to actual prospect activity.

Setup guide

Set up CONSENSUS 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 CONSENSUS tools at runtime.
3

Create your Agent

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

Run the agent

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

It exposes your demo analytics as callable tools for your agent. The OpenAI Agents SDK then executes these functions to read engagement data from your dashboard.

Yes, by pulling lists of sent invitations and demo analytics into your agent's context. The agent uses this to draft personalized messages based on specific feature views.

Absolutely. Since it's a standard MCP Server, the SDK auto-discovers all six tools, letting your agent run `list_users` or `list_demos` without any manual configuration.

You configure the server via an HTTP URL in your agent constructor. It initiates requests only when the agent needs data to complete a task.

The server transmits only the specific demo metadata and user lists requested by your agent. All traffic is scoped to your endpoint and handled through Vinkius's zero-trust gateway.

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