How to Use the Countly MCP in Google ADK

Q: Setting up Countly with Google ADK?

Use the McpToolset class to point at your server. Your agent configuration then includes this toolset in the tools list. It works over HTTP or Stdio depending on your infrastructure.

Q: Can Google ADK agents read Countly drill data?

The server provides the readdrill tool for this exact purpose. Your agent calls it, and the data is returned for further reasoning within your Gemini models.

Q: Does this MCP Server allow Google ADK to update users?

It does. You use updateuserdetails to sync information. Your agent modifies the user profile, and the change is reflected in your analytics dashboard immediately.

Q: Is Google ADK compatible with Countly event recording?

Yes, recordevents is fully supported. Your agent generates the action data, and the tool sends it to the server. It makes your agents active participants in your data collection.

Bring Countly behavioral metrics into your Google ADK agent flows and cloud infrastructure.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Countly MCP to Google ADK

Create your Vinkius account to connect Countly 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 Countly with Google ADK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Google ADK agents accessing Countly sessions

Your agent can start or stop user tracking with `begin_session` and `end_session` calls. It ensures your analytics reflect the exact state of your cloud-hosted applications. Use `update_session` to maintain heartbeat signals for long-running user interactions. This keeps your engagement data accurate as your agent processes multi-turn requests.

Fetching Countly metrics via Google ADK

Call `read_metrics` to grab high-level summaries of your user base. Your agent uses this data to make informed decisions about resource allocation or feature prioritization. Custom events are pulled using `read_events` so your logic stays grounded in current activity. It connects your agent directly to the raw data sitting in your analytics backend.

Deep segmentation with Countly and Google ADK

Execute `read_drill` to filter through your analytics data based on complex logic. Your agent interprets these segments to provide specific answers regarding user behavior. Recording new events happens via `record_events` inside your agent logic. It allows your system to log its own findings directly into your existing analytics stream.

Setup guide

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

Use the `McpToolset` class to point at your server. Your agent configuration then includes this toolset in the `tools` list. It works over HTTP or Stdio depending on your infrastructure.

The server provides the `read_drill` tool for this exact purpose. Your agent calls it, and the data is returned for further reasoning within your Gemini models.

We rely on token-based authentication for every request. Your analytics data, including user event logs, is never stored in the agent's memory. It is retrieved, processed, and cleared.

It does. You use `update_user_details` to sync information. Your agent modifies the user profile, and the change is reflected in your analytics dashboard immediately.

Yes, `record_events` is fully supported. Your agent generates the action data, and the tool sends it to the server. It makes your agents active participants in your data collection.

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