How to Use the Deterministic Fair-Share Tip Splitter MCP in AutoGen

Q: Does the tool handle edge cases like tax on specific items?

The splitbill tool calculates the proportion based on the item cost, ensuring tax and tip are distributed according to the total bill weight.

Debate your bill splits in AutoGen using the Deterministic Fair-Share Tip Splitter for consensus-driven math.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Deterministic Fair-Share Tip Splitter MCP to AutoGen

Create your Vinkius account to connect Deterministic Fair-Share Tip Splitter 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.

GDPR Free for Subscribers

Setup Deterministic Fair-Share Tip Splitter with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Multi-agent debate in AutoGen

Let your AutoGen agents negotiate the tip percentage or tax split. The `split_bill` tool provides the deterministic math that agents use to reach a final consensus. Agents challenge each other until the numbers align. You get a result that accounts for every diner's specific items and the total bill balance.

Autonomous bill resolution in AutoGen

Configure an AutoGen team to handle the entire split process. One agent feeds the receipt data to the `split_bill` tool while another verifies the final math. This removes the need for manual oversight. Your agents work together to ensure the split is fair and the remainders are handled correctly.

Consensus-based math for AutoGen

Use the `split_bill` tool as a source of truth during agent deliberation. When agents disagree on the total, they call this tool to settle the math definitively. This keeps your AutoGen systems focused on the facts. The tool provides the precise output required to end the debate and finalize the payment.

Setup guide

Set up Deterministic Fair-Share Tip Splitter 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 Deterministic Fair-Share Tip Splitter 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="Deterministic Fair-Share Tip Splitter_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Deterministic Fair-Share Tip Splitter 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="Deterministic Fair-Share Tip Splitter_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Deterministic Fair-Share Tip Splitter 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 tip-splitter. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Deterministic Fair-Share Tip Splitter now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Deterministic Fair-Share Tip Splitter MCP in AutoGen

Absolutely. You can have one agent propose a tip percentage and another verify the math using the `split_bill` tool until they agree on the final numbers.

Pass the server tools to your AssistantAgent constructor. The adapter handles the schema so your agents can invoke the split function immediately.

Yes. The agents will format your item list into the required JSON array before calling the tool, ensuring the math is always accurate.

The `split_bill` tool calculates the proportion based on the item cost, ensuring tax and tip are distributed according to the total bill weight.

It operates in a sandbox with no persistent storage. Your sensitive item and cost data are transient and inaccessible to outside parties.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.