How do I add the Inflation-Adjusted Return Calculator to AutoGen?

Register the tools using the MCP adapter for AutoGen. You can then pass the tools directly to your assistant agents.

How to Use the Inflation-Adjusted Return Calculator MCP in AutoGen

Force your AutoGen agents to debate real financial yields instead of nominal lies using this MCP.

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Works with every AI agent you already use

…and any MCP-compatible client

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Connect Inflation-Adjusted Return Calculator MCP to AutoGen

Create your Vinkius account to connect Inflation-Adjusted Return Calculator 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 Inflation-Adjusted Return Calculator with AutoGen

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Resolve financial debates with AutoGen agents

The `get_real_return_percentage` tool resolves arguments between agents by calculating the actual yield using the Fisher equation. It cuts through optimistic projections with cold math. When your investment agent proposes a portfolio, your risk agent can call this tool to challenge the real returns. This consensus-driven approach keeps your financial plans realistic.

Let agents calculate absolute cash losses

The `compute_absolute_inflationary_erosion` tool calculates the exact currency units lost to inflation over time. It gives agents a clear metric of wealth destruction. One agent can present a cash-heavy strategy, while another uses this tool to prove how much money is actually going down the drain. It makes debate outcomes quantifiable.

Evaluate purchasing power ratios in workflows

The `calculate_purchasing_power_ratio` tool calculates the percentage of purchasing power preserved over a given timeframe. It provides a standard metric for comparing different asset classes. Your agents can use this ratio to rank inflation-hedged assets against cash. It ensures your autonomous systems make decisions based on real purchasing power.

Setup guide

Set up Inflation-Adjusted Return Calculator 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 Inflation-Adjusted Return Calculator 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="Inflation-Adjusted Return Calculator_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Inflation-Adjusted Return Calculator 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="Inflation-Adjusted Return Calculator_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Inflation-Adjusted Return Calculator data")
    print(result.messages[-1].content)

Get your connection token →

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