How to Use the Founder Vision Prover MCP in AutoGen

Deploy a multi-agent debate in AutoGen to cross-examine startup pitches and validate unit economics before investing.

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Connect Founder Vision Prover MCP to AutoGen

Create your Vinkius account to connect Founder Vision Prover to AutoGen 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 AutoGen

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Debate Startup Viability via the MCP Server

The `validate_founder_vision` tool provides the objective baseline for your AutoGen agents to debate whether a startup has a real customer hack or just a superficial pitch. One agent can act as a skeptical YC partner running the validation, while another defends the founder's growth assumptions. This multi-agent debate forces a deep analysis of the bottom-up TAM, preventing simple agreement on lazy top-down market sizing. The agents use the tool's strict mathematical outputs to negotiate a final consensus on whether to proceed.

Cross-Examine Cohort Retention Curves

Your AutoGen agents use the `validate_founder_vision` tool to scrutinize Month 3 cohort retention and gross margins. An underwriting agent can run the tool to expose leaky buckets, while a growth agent evaluates the wedge-and-expand potential. By forcing the agents to argue using the MCP server's specific metrics, you avoid subjective bias in your investment decisions. The agents will only agree to approve the startup if the cohort data meets the strict SaaS or consumer benchmarks.

Challenge CAC Moats and Payback Periods

The `validate_founder_vision` tool helps your AutoGen agents identify zombie economics by calculating the exact CAC payback period. A finance agent runs the tool to check if the capital cycles within 12 months, challenging any optimistic projections from the marketing agent. If the payback period exceeds the limit, the finance agent uses the tool's output to veto the investment. This structured debate ensures that your agents catch distribution naivety before finalizing their joint recommendation.

Setup guide

Set up Founder Vision Prover MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Founder Vision Prover tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Founder Vision Prover_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Founder Vision Prover data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Founder Vision Prover_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Founder Vision Prover data")
    print(result.messages[-1].content)

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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 AutoGen

One agent runs the validation tool to calculate metrics like bottom-up TAM and retention. The other agents then use this structured output to debate the startup's viability and negotiate a final rating.

Yes. You register the tool with your AssistantAgent, allowing any agent in the group chat to trigger the MCP validation when a pitch deck is analyzed.

Install the extension, use the MCP streamable HTTP server parameters with your Vinkius URL, and pass the adapter tools directly to your agent constructor.

The agents will continue to debate, using the tool's strict metrics to challenge each other's assumptions until they reach a consensus or hit the max round limit.

Yes, all unit economics, customer hacks, and cohort retention metrics are processed inside secure, zero-trust V8 isolates. The data never leaves the ephemeral execution environment.

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