How to Use the Chargify MCP in Google ADK

Q: How do I set up the Google ADK to use the Chargify MCP Server?

You import McpToolset and point it to the server URL provided by Vinkius. Then you pass that toolset into your LlmAgent's tools parameter. The agent will then have access to all the Chargify functions.

Q: Can I limit which Chargify tools my agent can use?

Yes, the Google ADK allows this. When you configure the McpToolset, you can pass in an optional toolnames filter to expose only a specific subset of tools, like listcustomers and getcustomerdetails, while hiding destructive ones.

Connect your Gemini agents to Chargify billing data with the Google Agent Development Kit. Act on your subscription data right inside Google Cloud.

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Connect Chargify MCP to Google ADK

Create your Vinkius account to connect Chargify 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 Chargify with Google ADK

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Sync Chargify Customers with BigQuery

Your Gemini agent can now be the bridge between Chargify and your data warehouse. Use the `list_customers` tool to pull all customer records from a Chargify site. From there, the agent can iterate through the list, grab full records with `get_customer_details`, and write the structured JSON directly into a BigQuery table. This creates a pipeline for keeping your internal customer records perfectly in sync with your billing platform. You can run it on a schedule or trigger it manually. Because it's your agent doing the work, you can customize the logic to handle specific data transformations before it lands in BigQuery.

Enterprise Subscription Automation

Give your Gemini agent high-level goals for managing Chargify subscriptions. Thanks to its long-context reasoning, you can ask it to 'Switch customer X to the enterprise plan and apply a credit.' The agent can then use `list_catalog_products` to find the right plan handle and `update_subscription_product` to perform the switch. This MCP Server provides the agent with the precise tools it needs to interact with Chargify's billing engine. You can filter the tools passed to your `LlmAgent` to restrict its capabilities, giving you granular control over what it can and can't do in your production environment.

Feed Billing Data into Vertex AI

Turn your raw Chargify data into actionable insights. Have your agent use `list_subscriptions` and `get_subscription_details` to gather MRR, billing cycles, and plan information. Then, it can feed this structured data directly into a Vertex AI model for churn prediction or revenue forecasting. Instead of building a separate ETL job, your agent acts as a live data connector. This gets you from raw billing events to model inputs in fewer steps. It's all happening inside your Google Cloud ecosystem, where your data already lives.

Setup guide

Set up Chargify 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 Chargify 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="Chargify_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Chargify 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 Chargify. 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 Chargify MCP in Google ADK

You import `McpToolset` and point it to the server URL provided by Vinkius. Then you pass that toolset into your `LlmAgent`'s `tools` parameter. The agent will then have access to all the Chargify functions.

Yes. You can load a large report or a list of instructions into your agent's context, and it can use the Chargify tools to execute complex, multi-step tasks. For example, it could process a CSV of 100 customers who need their subscriptions updated.

Its native integration with the Google Cloud ecosystem is the key. Your Gemini agent can pull data from Chargify and immediately use it with BigQuery or Vertex AI without leaving your environment. It's built for enterprise-scale tasks.

Yes, the Google ADK allows this. When you configure the `McpToolset`, you can pass in an optional `tool_names` filter to expose only a specific subset of tools, like `list_customers` and `get_customer_details`, while hiding destructive ones.

Absolutely. The server is designed to only handle specific subscription data like MRR, billing cycles, and customer identifiers. It does not touch payment instruments. Each request runs in an isolated sandbox on Vinkius, and the connection to your Google Cloud environment is secured by your ADK setup.

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