How to Use the Founder Vision Prover MCP in OpenAI Agents SDK

Q: How do I configure Founder Vision Prover with OpenAI Agents SDK to stop bad investments?

You register the MCP server in your Python code using MCPServerStreamableHttp and pass it to your Agent constructor. The agent auto-discovers the validatefoundervision tool and runs it against raw text pitches.

Q: How does Founder Vision Prover handle concurrent requests from OpenAI Agents SDK?

You can run parallel evaluations by setting cacheToolsList=True for better performance. The SDK handles the concurrent execution of the validation tool across hundreds of incoming pitch decks.

Stop letting your OpenAI Agents SDK run wild on bad ideas. Force your agents to run brutal unit economic checks before executing.

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Connect Founder Vision Prover MCP to OpenAI Agents SDK

Create your Vinkius account to connect Founder Vision 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 Founder Vision Prover with OpenAI Agents SDK

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Spot the behavioral void with OpenAI Agents SDK

The `validate_founder_vision` tool acts as a ruthless filter inside your agentic loops. When an agent processes a startup pitch or a new product brief, this tool forces it to look for a real customer hack instead of vague feelings of frustration. Your agent looks for the exact workaround, the exact price point, and the manual system that the customer is currently using to survive. By deploying this check directly within your automated workflows, you prevent your agents from greenlighting weak ideas. You get immediate validation because the tool rejects any proposal that lacks hard, behavioral evidence of pain.

Calculate bottom-up TAM using this MCP Server

This tool replaces lazy market-sizing slides with cold, hard multiplication. Your agent runs `validate_founder_vision` to calculate reachable customers multiplied by annual contract value, forcing a wedge-and-expand strategy if the total is under $100 million. Integrating this math into your OpenAI Agents SDK pipeline stops your system from relying on useless top-down reports. You get a transparent math check that runs automatically during the ingestion phase.

Enforce strict retention physics and unit economics

The `validate_founder_vision` tool analyzes cohort metrics to separate real traction from vanity signups. It demands a Month 3 cohort retention rate above 80% for software and rejects any payback period that stretches past 12 months. Your agent runs these checks asynchronously using the SDK's built-in guardrails to block unviable business models before they reach your investment committee. This keeps your pipeline clean without requiring manual spreadsheet audits.

Setup guide

Set up Founder Vision 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 Founder Vision Prover tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Founder Vision 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 Founder Vision 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="Founder Vision Prover Agent",
            instructions="You have access to Founder Vision Prover tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Founder Vision Prover. 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.

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Common questions about Founder Vision Prover MCP in OpenAI Agents SDK

You register the MCP server in your Python code using `MCPServerStreamableHttp` and pass it to your Agent constructor. The agent auto-discovers the `validate_founder_vision` tool and runs it against raw text pitches.

You can run parallel evaluations by setting `cacheToolsList=True` for better performance. The SDK handles the concurrent execution of the validation tool across hundreds of incoming pitch decks.

The validation tool returns a failed status with detailed reasons. Your agent can read this output to automatically tag the pitch as high-risk or reject it outright.

You can set up your agent to pause and ask for human input when the tool flags a startup with a payback period over 12 months. This lets you manually review edge cases where unit economics look tight.

All startup pitch details, retention metrics, and customer hacks stay inside the V8 Isolate Sandbox. Vinkius runs this MCP server in an ephemeral environment, meaning no raw economics data is saved or shared with third parties after the tool execution finishes.

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