How to Use the Unanet MCP in Google ADK

Q: What specific Unanet data types are available via Google ADK?

You get access to projects listings, employee details from users, time records via timesheets, and financial information through the expenses tool. It covers all major operational areas.

Q: Does the Google ADK support fetching multiple types of records from Unanet at once?

Yes. You can structure your agent to call projects and then immediately follow up with timesheets, creating multi-step processes without losing context.

Connect your enterprise agents to Unanet data using the Google ADK.

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Connect Unanet MCP to Google ADK

Create your Vinkius account to connect Unanet 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 Unanet with Google ADK

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List Projects and User Details

Your agent can list all projects in Unanet by calling `projects`. This information is crucial for any analysis, letting you know exactly what work scopes are active. It also uses the `users` tool to pull a roster of employees. Since this MCP Server connects through Google Cloud, your agents get immediate access to that structured data.

Process Time and Expense Data

The ADK enables deep dives into employee time using the `timesheets` tool. You can ask your agent to list timesheet records for a specific user, making resource tracking straightforward. For financial reviews, calling `expenses` lists expense reports linked to a user. This lets you aggregate and analyze spending directly in BigQuery.

Run Full Scope Operational Reports

The MCP Server supports listing all core records—projects, users, timesheets, and expenses. Because this runs on Google Cloud, your agent can treat these four tools as a unified dataset. This structure means you don't have to build multiple connections; the ADK handles calling out to the correct tool within the Unanet MCP Server.

Setup guide

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

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Common questions about Unanet MCP in Google ADK

Since this runs on Google Cloud, your agents connect directly to BigQuery. You can hold massive amounts of context (1M+ tokens) while running reports against the MCP Server's tools.

You get access to `projects` listings, employee details from `users`, time records via `timesheets`, and financial information through the `expenses` tool. It covers all major operational areas.

Absolutely. The integration is built for enterprise use on Google Cloud infrastructure, ensuring robust handling of your sensitive project and employee data.

Yes. You can structure your agent to call `projects` and then immediately follow up with `timesheets`, creating multi-step processes without losing context.

The server touches operational records: project metadata, user profiles, time logs, and expense details. All is structured for enterprise-grade analysis.

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