How to Use the CaptivateIQ MCP in Google ADK

Run long-context Gemini reasoning over your CaptivateIQ compensation plans and BigQuery tables using the Google ADK.

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Connect CaptivateIQ MCP to Google ADK

Create your Vinkius account to connect CaptivateIQ to Google ADK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup CaptivateIQ with Google ADK

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Cross-reference BigQuery with the CaptivateIQ MCP Server

This MCP Server provides the `list_employees` tool to pull active sales reps and their plan designations directly into your Google ADK agent. Your agent queries BigQuery for closed-won opportunities, then matches them against the compensation rules retrieved from CaptivateIQ. Using the Gemini long-context window, your agent processes thousands of rows of sales data at once. You feed both the BigQuery output and the `list_payout_statements` results into a single context window to spot discrepancies instantly.

Analyze complex calculation sheets with Gemini

The `list_worksheets` tool exposes the underlying math of your commission plans directly to your Google ADK agent. Instead of copying formulas into a prompt, your agent uses `list_workbooks` to locate the correct file and pulls the raw structure. This direct integration with the MCP Server allows enterprise agents running on Google Cloud to explain complex commission payouts to managers. The agent reads the raw worksheet data, maps the logic, and generates clear explanations without manual spreadsheet work.

Track inquiry trends across your sales force

The `list_commission_inquiries` tool pulls active disputes so your Google ADK agent can categorize them. Your agent scans employee profiles using `get_employee_details` to find out if specific teams are disputing the same commission rules. This automated analysis helps you fix broken formulas before they impact morale. The agent connects to your cloud databases, compares historical dispute rates, and flags systematic issues in your plan designs.

Setup guide

Set up CaptivateIQ 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 CaptivateIQ 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="CaptivateIQ_agent",
    model="gemini-2.0-flash",
    instruction="You have access to CaptivateIQ tools via MCP.",
    tools=mcp_tools,
)

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 CaptivateIQ. 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 CaptivateIQ MCP in Google ADK

Use the McpToolset class with StreamableHttpServerParameters pointing to your Vinkius URL. Pass this toolset into your LlmAgent instance, and Gemini will automatically discover tools like `list_commission_payouts`.

The McpToolset constructor allows you to pass a tool name filter. You can choose to expose only `get_account_status` and `list_payout_statements` to keep your agent focused.

Gemini's 1M+ token context window easily handles large datasets from `list_employees`. The Google ADK passes the raw tool outputs directly into the model context without truncation.

It does. While Stdio works for local development, you should use the Streamable HTTP transport when hosting your enterprise agents on Google Cloud Run to connect to Vinkius.

Yes, all data transit is encrypted, and Vinkius executes the server inside a zero-trust sandbox. Your payroll numbers, employee plans, and commission details are processed ephemerally and never used to train base models.

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