How to Use the Station F Global Prover MCP in AutoGen

Facilitates consensus-driven decisions by challenging plans with Station F Global Prover's critical axes.

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Connect Station F Global Prover MCP to AutoGen

Create your Vinkius account to connect Station F Global Prover to AutoGen — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Station F Global Prover with AutoGen

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Debating Market Ambition

You can set up a multi-agent conversation where one agent proposes a plan, and another uses `validate_stationf_global` to challenge it based on the 'Continental Ambition' axis. The agents then debate until consensus is reached. This simulates a board meeting where every proposal must withstand rigorous scrutiny from multiple perspectives.

Challenging Capital Assumptions

Use three agents: one for Finance, one for Operations, and the Prover. The Finance agent proposes funding numbers, but the Prover forces it to check 'Capital Gluttony' rules (e.g., ROI per euro must be 8x higher). The negotiation process naturally pushes all participants toward lean, high-return models.

Consensus on Regulatory Moats

One agent acts as the 'Risk Officer,' and another acts as the 'Market Entry Specialist.' The Risk Officer calls `validate_stationf_global` to check regulatory compliance. If the Prover flags a vulnerability, the agents must debate how to build that specific barrier into the plan. This forces deep discussion on making regulations assets, not liabilities.

Setup guide

Set up Station F Global 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 Station F Global 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="Station F Global Prover_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Station F Global 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="Station F Global Prover_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Station F Global 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 Station F Global 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 Station F Global Prover MCP in AutoGen

It provides an objective, expert-level critique that agents must debate. This elevates the conversation from simple data retrieval to high-stakes strategic negotiation.

Yes. You can assign the role of 'Global Strategy Reviewer' to a dedicated agent whose only function is to call `validate_stationf_global` and force critical thinking on all axes.

It handles business models, operational expenditure forecasts, competitive regulatory landscapes (e.g., REACH), and market size calculations.

By making the Prover a mandatory part of the debate cycle, you ensure that every final decision has been vetted for continental potential and capital efficiency.

It guides developers to build conversations where the answer isn't obvious. The system must reach consensus *after* being challenged by the five rigorous axes of global strategy.

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