How to Use the Pricing Strategy Prover MCP in Google ADK

Bring enterprise-grade pricing logic to your Google ADK agents. Validate WTP and unit economics in your GCP environment.

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Connect Pricing Strategy Prover MCP to Google ADK

Create your Vinkius account to connect Pricing Strategy Prover 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 Pricing Strategy Prover with Google ADK

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Identify value metrics with Google ADK

Stop charging based on what competitors do. Use `validate_pricing_strategy` to find the exact unit that scales with your customer's success, whether that's storage, events, or revenue processed. Your agent uses this tool to audit your pricing structure against actual value delivered. If you are charging for seats but delivering infrastructure uptime, the tool flags the disconnect immediately.

Verify segment-specific pricing for enterprise

Freelancers and enterprises perceive value differently. This tool forces you to implement feature fencing to prevent cross-segment arbitrage and ensure you aren't leaving money on the table. Google ADK agents can use this to check if your tiered pricing correctly distinguishes between low-value users and enterprise accounts. It ensures your enterprise tier justifies its cost with actual SLA and feature requirements.

Calculate real LTV for Google ADK workflows

Adjusting LTV for gross margin is non-negotiable. This tool calculates your unit economics to ensure you maintain a healthy 3x LTV/CAC ratio and a 12-month payback period. By running this in your agent, you ensure your business model isn't just a collection of guesses. It forces you to account for heavy compute costs, ensuring your unit economics are actually sustainable.

Setup guide

Set up Pricing Strategy Prover 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 Pricing Strategy Prover 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="Pricing Strategy Prover_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Pricing Strategy Prover 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 Pricing Strategy Prover. 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 Pricing Strategy Prover MCP in Google ADK

Connect the server via the McpToolset in your Google ADK code. Once connected, your agent can call the validation tool to audit your pricing logic.

Absolutely. It validates your enterprise packaging strategies, including feature fencing and value-based pricing models, to ensure you capture the surplus correctly.

The current version focuses on USD calculations. You should normalize your inputs to USD before passing them to the tool for analysis.

You provide N= sample size data from your interviews. The tool applies Van Westendorp or Gabor-Granger logic to calculate optimal price points.

Your financial data stays local to your request. The server operates in an ephemeral sandbox and does not log your sensitive unit economics metrics.

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