How to Use the Kippy MCP in Google ADK

Q: How do I connect the Google ADK to the Kippy MCP server?

It's straightforward. You create an McpToolset instance using your Vinkius MCP server URL and pass it into your LlmAgent. The ADK handles the connection and tool discovery from there.

Connect Google ADK agents to your Kippy data to run performance analysis with the power of Gemini and BigQuery.

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Connect Kippy MCP to Google ADK

Create your Vinkius account to connect Kippy 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 Kippy with Google ADK

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Query performance data like a database

Treat your Kippy performance data as a queryable source for your Google agent. The agent can use Gemini's long-context window to analyze data from multiple tool calls at once. Ask it to `list_kpis` and then cross-reference the results with `list_kpi_scores` for a full picture. This is perfect for complex questions. Your agent can pull from `list_projects`, `list_teams`, and `list_users` to build a complete snapshot of organizational structure and performance without you touching a single dashboard.

Integrate Kippy data into Google Cloud

The Google ADK makes it easy to pipe Kippy data into your existing cloud setup. An agent can fetch team metrics with `list_team_scores` and `list_project_scores`, then pass that data directly to a BigQuery table for long-term storage and analysis. This isn't just about moving data. It's about acting on it within your environment. You can build agents that listen for changes in Kippy's `list_audit_logs` and trigger Cloud Functions or other downstream workflows.

Build enterprise agents with this Google ADK MCP Server

This Kippy MCP server gives your agent the tools to manage enterprise-scale performance reviews. It can `list_appraisals` for an entire department or check on required `list_competencies` for a specific role. Because it's running on Google ADK, your agent can handle these large datasets. It can summarize feedback from `list_feedback` across hundreds of entries or track progress against `list_annual_scores` for the whole company.

Setup guide

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

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Common questions about Kippy MCP in Google ADK

It's straightforward. You create an `McpToolset` instance using your Vinkius MCP server URL and pass it into your `LlmAgent`. The ADK handles the connection and tool discovery from there.

Yes, that's a primary use case. Your agent can fetch performance data from Kippy using tools like `list_kpi_scores` and then run a BigQuery job to join it with other business data for deeper insights.

You can instruct your agent to monitor specific metrics. For example, tell it to 'check `list_project_scores` for the Phoenix project every Monday and summarize the changes.' The agent will use the available Kippy tools to do the work.

Gemini's large context window allows your agent to process more information at once. It can pull data from `list_users`, `list_teams`, and `list_appraisals` in a single session to answer complex, multi-part questions about your organization.

Absolutely. The connection to the Vinkius-hosted server is encrypted. Your sensitive HR data, such as `list_appraisals` and `list_feedback` entries, is processed within an isolated, ephemeral environment that doesn't persist your information.

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