How to Use the Option Pool Shuffle Simulator MCP in AutoGen

Q: How do I load the Option Pool Shuffle Simulator into AutoGen?

Run pip install -U "autogen-extmcp". Use mcpservertools with StreamableHttpServerParams to fetch the tool definitions.

Let AutoGen agents debate term sheet dilution using hard math.

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Connect Option Pool Shuffle Simulator MCP to AutoGen

Create your Vinkius account to connect Option Pool Shuffle Simulator 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 Option Pool Shuffle Simulator with AutoGen

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Founder Agent Math

A simulated founder agent calls `compute_pre_money_scenario` to see exactly how much equity they lose under standard VC terms. The tool calculates the exact share distribution when the option pool comes out of the existing cap table. AutoGen excels at this adversarial setup. The founder agent receives the math and immediately formulates an argument against the proposed valuation structure.

Investor Agent Counterproposals

The opposing agent needs its own data. It triggers `compute_post_money_scenario` to model the alternative where everyone shares the dilution. Vinkius hosts over 4,000 tools in its managed catalog. Your AutoGen setup connects once and your agents can pull financial APIs, legal checkers, and data scrapers into their negotiation debates.

Resolve Debates With This MCP Server

Consensus requires objective comparison. The moderator agent executes `compare_shuffle_impact` to generate a side-by-side breakdown of the two competing term sheets. The agents review the delta and negotiate a middle ground. The McpToolAdapter handles the schema conversions so your agents focus entirely on the financial strategy.

Setup guide

Set up Option Pool Shuffle Simulator 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 Option Pool Shuffle Simulator 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="Option Pool Shuffle Simulator_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Option Pool Shuffle Simulator data")
print(result.messages[-1].content)

Get your connection token →

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="Option Pool Shuffle Simulator_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Option Pool Shuffle Simulator data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Option Pool Simulator. 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 Option Pool Shuffle Simulator MCP in AutoGen

Run pip install -U "autogen-ext[mcp]". Use mcp_server_tools with StreamableHttpServerParams to fetch the tool definitions.

Yes. You pass the tool list to any AssistantAgent constructor. Different agents can run different calculations during their debate.

The Vinkius endpoint fully supports streamable HTTP transports. Your agents get the calculation results without blocking the conversation thread.

Vinkius manages the infrastructure for 4,000 MCPs. You configure the catalog connection once and your agent swarm gets immediate access to every tool.

The endpoints process raw valuation numbers and share prices. The system runs these calculations statelessly and retains zero record of the negotiation variables.

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