How to Use the ROAS Calculator MCP in CrewAI

Q: How do I use ROAS Calculator with CrewAI?

You define a crew where one agent calls calculateroas first. Then, another specialized agent takes that output and feeds it into the final analysis step.

Q: Can I validate break-even points using CrewAI?

Yes, assign a 'Risk Assessment Agent' to call calculatebreakevenroas. This agent determines the necessary ROAS based on a given contribution margin and reports it.

Q: Does CrewAI help benchmark my ad spending?

Absolutely. The crew can use gettargetbenchmark to pull industry data, letting your 'Moderator Agent' compare the calculated ROAS against the required market standard.

Automated ad analysis with CrewAI's collaborative ROAS Calculator.

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Setup ROAS Calculator with CrewAI

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Calculate overall Return on Ad Spend.

Give your 'Finance Analyst' agent the job of calculating ROAS using `calculate_roas`. This tool requires media spend and source revenue to provide a definitive performance metric. The resulting data can then be passed to the 'Reporting Agent,' which structures it into an actionable summary for the user.

Determine break-even ad spending limits.

To prevent overspending, use `calculate_break_even_roas`. This tool requires a contribution margin to figure out the absolute minimum ROAS you need just to stay afloat. The 'Monitoring Agent' can watch this calculation and ensure that no spending exceeds the calculated threshold without approval.

Benchmark against industry standards.

The `get_target_benchmark` tool lets your crew pull in external target ROAS data for a specific business type. This gives instant, objective context to the performance numbers. The 'Research Agent' uses this benchmark result to guide the final conclusion, telling the user if their current efforts are competitive.

Setup guide

Set up ROAS Calculator MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke ROAS Calculator tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="ROAS Calculator Analyst",
    goal="Access and analyze ROAS Calculator data via MCP.",
    backstory="Expert analyst with direct ROAS Calculator access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent ROAS Calculator transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="ROAS Calculator Analyst",
        goal="Access and analyze ROAS Calculator data via MCP.",
        backstory="Expert analyst with direct ROAS Calculator access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent ROAS Calculator transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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 ROAS 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.

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Common questions about ROAS Calculator MCP in CrewAI

You define a crew where one agent calls `calculate_roas` first. Then, another specialized agent takes that output and feeds it into the final analysis step.

It handles numerical inputs like media spend and source revenue figures. The shared memory of the crew ensures these financial numbers flow cleanly between specialized agents.

Yes, assign a 'Risk Assessment Agent' to call `calculate_break_even_roas`. This agent determines the necessary ROAS based on a given contribution margin and reports it.

Absolutely. The crew can use `get_target_benchmark` to pull industry data, letting your 'Moderator Agent' compare the calculated ROAS against the required market standard.

It is. You can build a full pipeline: one agent calculates performance, another checks the break-even point, and a third compares it all to external benchmarks.

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