How to Use the FastSpring MCP in Google ADK

Q: How does FastSpring integrate with Google ADK for enterprise agents?

The server exposes tools directly to the LlmAgent constructor via McpToolset. It integrates like any other native Google Cloud service.

Q: Can FastSpring tools in Google ADK read BigQuery data?

You can combine the outputs of listaccounts with your BigQuery datasets. The agent handles the data correlation internally.

Native commerce integration for Google ADK agents.

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Connect FastSpring MCP to Google ADK

Create your Vinkius account to connect FastSpring 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 FastSpring with Google ADK

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Vertex AI-ready commerce tools

Connect your Google ADK agent to the platform using `McpToolset`. It bridges your commerce data with your Google Cloud infrastructure. Use `get_account_details` to feed customer data into Gemini's long-context window. You get deep reasoning over account histories without moving data between silos.

Enterprise-grade subscription management

Update customer plans with `update_subscription_plan` directly from your agent's decision loop. It makes managing enterprise billing cycles trivial. Trigger `cancel_subscription` based on automated churn analysis. Your agent performs these actions with high precision, ensuring no billing discrepancies occur.

Commerce data visibility

Map your product catalog using `list_catalog_products`. This provides your agent with a clear view of your available offerings. Fetch transaction data via `get_order_details` to track order limits. This MCP Server ensures your agents stay aligned with your actual sales data.

Setup guide

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

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Common questions about FastSpring MCP in Google ADK

The server exposes tools directly to the `LlmAgent` constructor via `McpToolset`. It integrates like any other native Google Cloud service.

You can combine the outputs of `list_accounts` with your BigQuery datasets. The agent handles the data correlation internally.

The Vinkius-hosted server handles the heavy lifting. You just provide the endpoint token, and the agent takes care of the rest.

It does. You can choose between Stdio and HTTP transports depending on your specific infrastructure needs.

All subscription identifiers and billing records are processed in isolation. The server ensures only your authenticated agent accesses this sensitive information.

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