How to Use the ChartMogul MCP in Google ADK

Q: How do I configure the Google ADK to fetch ChartMogul data?

You initialize McpToolset with your Vinkius HTTP MCP server parameters and pass it to your LlmAgent. This exposes tools like getsummarymetrics directly to Gemini models.

Q: Can I limit the ChartMogul tools exposed to the Google ADK?

Yes, you can use the optional toolnames filter when setting up your toolset. This lets you restrict your agent to read-only tools like getchurnrates and hide write operations.

Run deep revenue analysis by connecting the Google ADK directly to your live ChartMogul data.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect ChartMogul MCP to Google ADK

Create your Vinkius account to connect ChartMogul 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.

GDPR Free for Subscribers

Setup ChartMogul with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Long-context revenue analysis with Google ADK

Gemini models can ingest massive amounts of data. By connecting this MCP Server, your agent can pull years of billing history using `get_arr_history` and `get_mrr_history` directly into its context window. Instead of exporting CSVs, the agent reads historical trends and correlates them with your BigQuery data. It uses `get_customer_count_history` to map user growth against your marketing campaigns.

Enterprise customer valuation pipelines

Your agent can look up individual customer values using `get_customer_ltv` and `get_customer_details`. This allows your Vertex AI pipelines to automatically score leads based on actual subscription history. By calling `list_subscription_plans`, your enterprise agents can match existing plans against usage metrics stored in Google Cloud, identifying accounts that are ready for an upgrade.

Automated billing reconciliation

Verify your data pipelines are operating correctly by calling `get_api_status` and `list_data_sources`. Your agents can monitor these endpoints to ensure that external payment gateways are writing to your dashboard correctly. When a discrepancy is found, the agent can run `list_customers` to find the missing profiles. It can then execute `create_customer_record` to align your records across systems.

Setup guide

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

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ChartMogul. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect ChartMogul now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about ChartMogul MCP in Google ADK

You initialize `McpToolset` with your Vinkius HTTP MCP server parameters and pass it to your `LlmAgent`. This exposes tools like `get_summary_metrics` directly to Gemini models.

Yes, you can use the optional `tool_names` filter when setting up your toolset. This lets you restrict your agent to read-only tools like `get_churn_rates` and hide write operations.

Yes, the framework supports both. However, since Vinkius hosts the server, you will want to use the Streamable HTTP transport option for cloud deployments.

Gemini's million-token context easily handles large arrays returned by `list_customers`. The model can analyze the entire customer list in a single pass without hitting token limits.

Your metrics never touch public LLM training sets. Vinkius runs the MCP server in an isolated V8 sandbox, and your private MRR and ARR numbers are processed purely within your secure Google Cloud VPC boundary.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript