How to Use the Hallucination Detector Prover MCP in OpenAI Agents SDK

Stop agentic drift in your OpenAI Agents SDK builds. Force verifiable source attribution and epistemic rigor on every output.

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Connect Hallucination Detector Prover MCP to OpenAI Agents SDK

Create your Vinkius account to connect Hallucination Detector Prover 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 Hallucination Detector Prover with OpenAI Agents SDK

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Enforce grounding in OpenAI Agents SDK

Your agent runs `validate_hallucination_grounding` before finalizing any response. It demands specific citations, author names, and publication dates for every factual claim. This stops the agent from relying on vague phrases like 'studies show'. If the agent cannot back a claim with a verifiable source, the tool flags it as an ungrounded hallucination.

Calibrate confidence for OpenAI Agents SDK

Each output gets a confidence score based on the evidence quality provided. The `validate_hallucination_grounding` tool treats a peer-reviewed RCT differently than an anonymous blog post. Your agent learns to distinguish between data-backed certainty and mere probability. It explicitly labels statements as facts or opinions so your end-users know exactly what they are reading.

Check internal logic in OpenAI Agents SDK

The `validate_hallucination_grounding` tool cross-references the entire agent response for contradictions. It catches discrepancies between claims made in different paragraphs. If the agent claims a value is 50ms in one sentence and 200ms in another, the tool blocks the transmission. You get consistent, verified data in every production agent pipeline.

Setup guide

Set up Hallucination Detector Prover 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 Hallucination Detector Prover tools at runtime.
3

Create your Agent

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

Run the agent

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

You connect it via the MCPServerStreamableHttp class in your Python setup. Once registered as a toolset, your agent automatically calls the grounding logic before delivering results.

There is a minor latency cost for the verification step. However, this is a necessary trade-off to ensure the factual integrity of your agentic outputs.

Yes, it forces the agent to provide specific DOIs or URLs for every claim. If the source is missing, the tool rejects the output as a hallucination.

The server operates at the tool execution layer. Any agent in your chain can invoke the validation check to verify its own internal reasoning.

The server treats your text strings as ephemeral inputs for validation. No raw query data is stored permanently, ensuring your sensitive business logic remains isolated.

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