How to Use the Whop MCP in Google ADK

Q: How do I track all Whop payments using Google ADK?

You run listpayments through the MCP Server. Because of the native BigQuery integration, these transaction records automatically populate your data warehouse for historical review.

Q: Can the MCP Server help with Whop promotional codes using Google ADK?

Absolutely. You use listpromocodes to pull all current discount codes into your long-context reasoning space. This lets your agent analyze usage patterns against product sales data.

Q: Does Whop support listing invoices with Google ADK?

Yes, you call listinvoices. This is crucial for accounting processes because it provides direct access to billing records that need to be mapped into your existing BigQuery schema.

Scale Whop operations across BigQuery with Google ADK.

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Connect Whop MCP to Google ADK

Create your Vinkius account to connect Whop 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 Whop with Google ADK

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Enterprise Membership Management via MCP Server

Your agent accesses member data by calling `list_memberships`. This allows your enterprise system to query current user status and subscription counts directly. The results feed into BigQuery, keeping all records centralized for long-context analysis.

Run Financial Reports using Google ADK

To get a full picture of revenue, run `list_payments`. This tool pulls payment transactions that can then be analyzed by Gemini models within your cloud environment. You're not just listing payments; you're preparing massive datasets for deep analysis.

Catalog Management with Google ADK

You need to list all available products? Call `list_products`. This tool provides the foundational data set that your Vertex AI pipelines use. It ensures that any new product added to Whop's catalog is immediately visible to your agent workflows.

Setup guide

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

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Common questions about Whop MCP in Google ADK

You run `list_payments` through the MCP Server. Because of the native BigQuery integration, these transaction records automatically populate your data warehouse for historical review.

Absolutely. You use `list_promo_codes` to pull all current discount codes into your long-context reasoning space. This lets your agent analyze usage patterns against product sales data.

The agent supports fetching user company details and general account info using the `get_me` tool. It’s a quick, reliable way to establish context before running larger analyses.

Yes, you call `list_invoices`. This is crucial for accounting processes because it provides direct access to billing records that need to be mapped into your existing BigQuery schema.

The server touches payment transaction data and membership status. When integrating, you control the scope of data retrieval using tool filters, ensuring only necessary records are passed to your Gemini models.

Use it with your favorite AI tools

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