How to Use the Influencer ROI Calculator MCP in AutoGen

Q: How do I assign different Influencer ROI Calculator tools to different agents in my AutoGen group chat?

When you configure each AssistantAgent, you specify which tools from the MCP it can use. You can give getengagementvaluation to your 'MarketingAgent' and getconversioneconomics to your 'FinanceAgent', ensuring they play their designated roles in the conversation.

Q: Is it possible for an agent with the Influencer ROI Calculator for AutoGen to propose a budget and have a human approve it?

Yes. You can set up a UserProxyAgent to represent you in the conversation. The agent team will debate and propose a budget using the MCP tools, and then the final recommendation will be presented to you for a go/no-go decision before any action is taken.

Let your agents debate influencer budgets. Use AutoGen to reach a consensus on campaign spending backed by hard financial data.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Influencer ROI Calculator MCP to AutoGen

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

GDPR Included with Plan

Setup Influencer ROI Calculator with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity Vinkius runs on Gemini

Gemini

Grok

Equip Your 'Marketing' Agent

Give one agent in your group chat the `get_engagement_valuation` tool. This agent can now join the conversation and argue for a campaign based on its projected Earned Media Value and audience size. Instead of making a vague pitch, the agent brings a specific number to the table. It sets a data-driven baseline for the debate, forcing other agents to respond with equally concrete evidence.

Arm the 'Finance' Agent

Introduce a second agent to act as a financial check. By giving it the `get_conversion_economics` tool, this agent can immediately challenge the marketing agent's proposal by calculating the projected CAC and profitability. This creates a healthy tension. The finance agent's job is to ask, "That's great reach, but will it be profitable?" This MCP provides the tools to have that exact argument, backed by numbers.

Let the 'Strategist' Agent Decide

A third agent can act as a tie-breaker. Give it the `compare_to_paid_social` tool to introduce objective, external benchmarks into the conversation. This agent’s role is to determine if the proposed influencer spend is more efficient than putting the same money into proven channels. This multi-agent debate leads to a more robust decision than any single agent could make. The final output is a consensus, stress-tested from multiple angles, all orchestrated through your AutoGen setup and this MCP Server.

Setup guide

Set up Influencer ROI 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 Influencer ROI 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="Influencer ROI Calculator_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

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

    result = await agent.run("List recent Influencer ROI Calculator 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 Influencer ROI Calculator. 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 Influencer ROI Calculator 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 Influencer ROI Calculator MCP in AutoGen

When you configure each `AssistantAgent`, you specify which tools from the MCP it can use. You can give `get_engagement_valuation` to your 'MarketingAgent' and `get_conversion_economics` to your 'FinanceAgent', ensuring they play their designated roles in the conversation.

Absolutely. You can create a 'CalculatorAgent' that runs a tool from the Influencer ROI Calculator, and a 'ValidatorAgent' that takes the output and the inputs to confirm the calculation is correct. This is a common pattern for building high-stakes, reliable multi-agent systems.

Yes. You can set up a `UserProxyAgent` to represent you in the conversation. The agent team will debate and propose a budget using the MCP tools, and then the final recommendation will be presented to you for a go/no-go decision before any action is taken.

Yes, that's the point of the conversation. When one agent calls a tool from this MCP, the result is posted as a message in the group chat. Other agents can then read that output and use it as context for their own replies or subsequent tool calls.

Your data—like campaign costs and conversion rates—is passed between agents inside your AutoGen environment. The Influencer ROI Calculator MCP only receives the data needed for a specific calculation and returns a result over a secure connection, without logging the specifics of your request.

Use it with your favorite AI tools

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

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript