How to Use the TrackingTime MCP in Google ADK

Q: How does the Google ADK handle TrackingTime reporting?

The MCP Server provides listtimeentries, which streams all historical time logs. Your agent reads this data and pushes it to BigQuery, where you build your final reports.

Q: Can I modify existing project details with the Google ADK?

Yes. The updatetask tool lets agents modify tasks, while createproject handles adding new ones. This ensures all structural changes are captured in your enterprise data flow.

Q: What kind of reporting can I generate with TrackingTime and the Google ADK?

You get full visibility into time logs using listtimeentries. Because this connects natively to BigQuery, you're not limited by report types; you write the query, and the agent executes it.

Q: How is user context managed when I use TrackingTime with the Google ADK?

Agents access listworkspaceusers to understand team roles. They also retrieve current identity data via getuserprofile, ensuring that time entries are always attributed correctly.

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Create your Vinkius account to connect TrackingTime 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 TrackingTime with Google ADK

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Automate Time Entry and Logging

The `list_time_entries` tool lets your agent pull historical logs directly into BigQuery. You can also use `add_time_entry` to inject new time data, making it available for immediate analysis. Since you're building enterprise agents on Google Cloud, this direct integration means raw time log data feeds straight into your existing data lake.

Manage Projects and Clients at Scale

Agents use `list_projects` to get a definitive list of all active projects. Furthermore, they call `list_customers` when they need to scope work down to a specific client account. This mechanism allows your Gemini agents to maintain context across massive datasets stored in BigQuery.

Track Work Status and Team Resources

Your agent uses `list_tasks` to verify current project tasks. It can also use `start_timer` or `stop_timer` for real-time tracking data, which is instantly available for analysis. This live operational data feeds directly into your Google Cloud environment, giving you immediate insight into resource utilization.

Setup guide

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

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by TrackingTime. 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.

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Common questions about TrackingTime MCP in Google ADK

The MCP Server provides `list_time_entries`, which streams all historical time logs. Your agent reads this data and pushes it to BigQuery, where you build your final reports.

Yes. The `update_task` tool lets agents modify tasks, while `create_project` handles adding new ones. This ensures all structural changes are captured in your enterprise data flow.

You get full visibility into time logs using `list_time_entries`. Because this connects natively to BigQuery, you're not limited by report types; you write the query, and the agent executes it.

Agents access `list_workspace_users` to understand team roles. They also retrieve current identity data via `get_user_profile`, ensuring that time entries are always attributed correctly.

This TrackingTime MCP Server touches project names, task details, and user profile information. The core structured data type is the time entry log itself.

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