How to Use the Keen MCP in Google ADK

Q: Does the Google ADK support Keen tool filtering?

Yes. You can use the toolnames filter to restrict the agent, ensuring it only uses a subset of Keen tools like countunique.

Bring Keen analytics into your Google ADK agent framework for deep data-driven reasoning.

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Connect Keen MCP to Google ADK

Create your Vinkius account to connect Keen 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 Keen with Google ADK

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Native Keen tool access for Google ADK

The `McpToolset` makes Keen functionality available to your Gemini-powered agents. Your agents can now query your event collections as easily as they query local variables. This approach maps Keen operations directly into the agent's tool library. You don't need to write glue code to bridge the gap between your event data and the Gemini model.

Advanced event processing in Google ADK

Run complex queries like `average_property` or `select_unique` to feed the agent's context window. It turns raw event logs into actionable insights on the fly. Because the agent performs these queries, it can adjust its reasoning based on the latest metrics. It changes the way your enterprise agents interpret user intent.

Manage project metadata with Google ADK

Use `list_saved_queries` to let the agent retrieve predefined reports. It knows exactly which saved analyses are relevant for a given user request. This keeps your agent informed about the project structure without hardcoding identifiers. It queries the Keen project configuration dynamically during runtime.

Setup guide

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

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Common questions about Keen MCP in Google ADK

It gives your Gemini agents a direct line to your event data. You get faster insights without moving data between your cloud infrastructure and the agent.

Yes. You can use the tool_names filter to restrict the agent, ensuring it only uses a subset of Keen tools like `count_unique`.

The connection uses your specific endpoint token. All traffic remains scoped to your project, preventing unauthorized access to your event stream.

While the agent framework manages context, you can implement application-level caching for frequent Keen queries to reduce API calls.

Your keys stay in your environment variables. The MCP server handles the signing, so the agent never touches your raw credentials.

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