How to Use the Deputy MCP in Google ADK

Q: Can Google ADK agents filter Deputy tool access?

Yes, you can pass a toolnames filter to the toolset. This restricts the agent to only using the functions you want it to perform.

Integrate Deputy with Google ADK for enterprise agents that reason over your workforce data on Google Cloud.

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Connect Deputy MCP to Google ADK

Create your Vinkius account to connect Deputy 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 Deputy with Google ADK

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Workforce analytics for Google ADK agents

Feed your Gemini models data from `list_completed_timesheets` to analyze labor trends. The model processes these records to identify gaps in your reporting. Your agent interprets this data alongside your other cloud sources. It provides insights based on actual hours recorded in the field.

Managing business locations in Google ADK

Agents identify which facility to query using `list_business_locations`. It maps your Google Cloud project data to the correct physical office. This allows the agent to scope its actions to specific sites. You avoid cross-contamination of shift data between different branches.

Searching staff records via Google ADK tools

Locate specific team members quickly using `search_employees_by_name`. The agent parses your request and fetches the matching profile details from the server. It handles the lookup logic so you don't write custom search code. You get the correct employee record back in a single step.

Setup guide

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

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Common questions about Deputy MCP in Google ADK

Use the McpToolset class to point your agent at the Deputy server URL. It bridges the gap between Gemini models and your workforce data on GCP.

Yes, you can pass a tool_names filter to the toolset. This restricts the agent to only using the functions you want it to perform.

The server supports both Stdio and HTTP transports. You choose the one that fits your Google Cloud deployment architecture.

The server acts as a gatekeeper for the Deputy API. It ensures the agent only sees the specific roster and timesheet data it needs for the current task.

It only touches names and shift timestamps. We enforce strict read-only access for all employee profiles to keep your workforce information private.

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