How to Use the Pricing Strategy Calculator MCP in Google ADK

Q: How do I configure the Pricing Strategy Calculator MCP within Google ADK?

Instantiate the McpToolset with the HTTP transport parameters pointing to the Vinkius managed endpoint. Then, pass this toolset to your LlmAgent configuration block so your Google agents can access the pricing calculations.

Run enterprise-scale pricing models directly on BigQuery data using Google ADK.

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Connect Pricing Strategy Calculator MCP to Google ADK

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

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Automate margin calculations from BigQuery

Pull raw cost data from your cloud warehouse and feed it directly to the MCP. Your agent executes `calculate_cost_plus_price` to find the minimum viable price point for any product SKU. This eliminates manual export steps. The agent reads the actual cost basis and outputs the required markup to hit your corporate margin goals.

Predict MRR shifts using Google ADK

Enterprise price changes require rigorous financial modeling before rollout. Your agent uses `predict_mrr_impact` to simulate how price adjustments will shift your monthly recurring revenue. The agent processes these projections in a long-context window. This allows it to compare multiple scenarios side by side for executive review.

Determine value-based pricing points

Evaluate customer segments by running `calculate_value_based_price` to align your pricing with actual economic utility. At the same time, the agent checks `calculate_competitive_price` to monitor where rivals are positioned. You get a balanced strategy that respects both customer value and market realities.

Setup guide

Set up Pricing Strategy 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 Pricing Strategy 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="Pricing Strategy Calculator_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Pricing Strategy Calculator tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Pricing Strategy Calculator MCP in Google ADK

Instantiate the `McpToolset` with the HTTP transport parameters pointing to the Vinkius managed endpoint. Then, pass this toolset to your `LlmAgent` configuration block so your Google agents can access the pricing calculations.

Yes, you can use the optional tool names filter when initializing the toolset in Google ADK. This lets you expose only specific pricing tools to your agent while hiding the rest.

Your Google agent can query your historical sales tables in BigQuery, format those rows, and pass them directly to the pricing tools. This creates an automated pipeline from raw cloud database records to pricing recommendations.

Yes, the toolset integration supports concurrent execution. You can run hundreds of pricing evaluations in parallel without blocking your main application loop.

All competitor price points and pricing variables are processed inside an isolated VPC running this MCP. We secure this traffic with TLS 1.3 encryption and guarantee that none of your proprietary market data is cached or logged.

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