How to Use the Lunatask MCP in Google ADK

Q: How do I link Lunatask to Google ADK?

You initialize the McpToolset with the server URL. Once connected, your agent can call tools like gettaskmetadata to see what tasks are pending.

Connect your Google ADK agents to Lunatask to organize tasks and habits within your existing enterprise data infrastructure.

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Connect Lunatask MCP to Google ADK

Create your Vinkius account to connect Lunatask 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 Lunatask with Google ADK

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Direct task control via Google ADK

Your agent can trigger `create_new_task` or `delete_task` to manage your queue programmatically. It integrates into your existing Google Cloud pipelines. This keeps your task list updated as your agent processes other data streams. It’s a direct link between your cloud logic and your personal productivity.

Habit logging for enterprise workflows

Use `track_habit_completion` to record your progress automatically. It’s a simple way to keep your habits synced with your agent's operations. Your agent executes the call whenever your criteria are met. It removes the friction of manual tracking in your daily routine.

Accessing Lunatask metadata securely

The server exposes `list_tasks_metadata` so your agent can reason about your workload. It provides the structure of your tasks without touching the private content. This keeps your data architecture clean. Your agent gets the context it needs while your journal entries stay encrypted and local.

Setup guide

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

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Common questions about Lunatask MCP in Google ADK

You initialize the `McpToolset` with the server URL. Once connected, your agent can call tools like `get_task_metadata` to see what tasks are pending.

Only metadata is visible. The server restricts access to task names and raw notes to maintain your privacy.

Yes, you can expose all of them. Use a tool filter if you want to limit your agent's access to specific operations like `update_existing_task`.

It relies on the Lunatask REST API design which separates encrypted content from metadata. Your agent never sees the unencrypted text.

Absolutely. The server runs as a standard MCP host, allowing your ADK-based agents to manage your personal productivity alongside your enterprise data.

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