How to Use the Content ROI Calculator MCP in Google ADK

Q: How do I configure the Content ROI Calculator with Google ADK?

Install the package via pip install google-adk first. Then wrap this MCP endpoint in McpToolset using StreamableHttpServerParameters and pass it to your agent.

Q: Can I restrict which tools the Content ROI Calculator exposes to Google ADK?

You can use the optional toolnames filter when setting up the toolset. This limits the agent to specific calculations if you want tighter control.

Connect your BigQuery marketing data to the Content ROI Calculator using Google ADK.

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Connect Content ROI Calculator MCP to Google ADK

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

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Setup Content ROI Calculator with Google ADK

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Perplexity Vinkius runs on Gemini

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Aggregate expenses with Google ADK

Enterprise marketing teams scatter their spend across a dozen different platforms. Compiling those numbers usually requires painful manual exports. Your LlmAgent can use `calculate_total_cost` to sum up the production hours and vendor invoices automatically. This gives your Gemini models a hard baseline to evaluate content efficiency across massive datasets.

Map search volume to pipeline

Traffic is a vanity metric unless you know how many visitors actually convert. You need to turn raw analytics into estimated sales figures. Running the `calculate_attributed_revenue` tool lets your agent translate organic sessions into projected revenue. You can feed that output directly into Vertex AI for broader market predictions via this MCP.

Determine payback periods via this MCP Server

Content is an investment that takes time to mature. Knowing exactly when an asset breaks even changes how you allocate future budgets. The `calculate_roi_summary` endpoint calculates the final return rate and time to profitability. Your agent can hold years of historical performance in its long context window while generating these insights.

Setup guide

Set up Content ROI Calculator MCP in Google ADK

Prerequisites

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

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Content ROI Calculator tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Content ROI Calculator_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Content ROI Calculator tools via MCP.",
    tools=mcp_tools,
)

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Content 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.

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Common questions about Content ROI Calculator MCP in Google ADK

Install the package via `pip install google-adk` first. Then wrap this MCP endpoint in `McpToolset` using `StreamableHttpServerParameters` and pass it to your agent.

You can use the optional `tool_names` filter when setting up the toolset. This limits the agent to specific calculations if you want tighter control.

Your agent can pull raw traffic numbers from BigQuery and feed them straight into the calculator. The framework handles the data movement natively.

The toolset works with both Stdio and HTTP transports. You choose the connection method that fits your cloud architecture.

The calculations happen securely within your defined environment. Your closed-won deal values and conversion rates are never broadcasted to third-party tracking services.

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