How to Use the Ellie Planner MCP in Google ADK

Feed project data from BigQuery straight into Ellie Planner using Gemini long-context reasoning and the Google ADK.

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Connect Ellie Planner MCP to Google ADK

Create your Vinkius account to connect Ellie Planner 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 Ellie Planner with Google ADK

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Enterprise Planning with Google ADK

The `list_tasks` tool lets your Gemini agent scan thousands of active project items to build a unified timeline directly inside your enterprise cloud environment. Google ADK connects this MCP Server to your Vertex AI models, allowing the agent to digest massive backlogs in a single reasoning window. Because Gemini handles over a million tokens, your agent can compare your live Ellie Planner board with raw datasets stored in BigQuery, making sure your visual schedules match your actual database records.

Automated Backlog Generation

The `create_task` tool enables your agent to generate new timeline entries based on external pipeline triggers. When a pipeline fails or a milestone is reached, the agent writes the update directly to your visual board. By using this MCP, your agent can use the `list_lists` tool to find the right board first, then populate it with specific labels fetched via `list_labels`. This keeps your engineering metrics and visual timelines perfectly aligned.

Dynamic Timeline Adjustments

The `update_task` tool allows your enterprise agent to shift project dates when external deadlines slip. Instead of manually dragging cards on a screen, your Google Cloud workflows trigger these adjustments programmatically. The agent verifies the change by calling `get_task` immediately after, ensuring the visual board matches your internal systems. If a task is no longer relevant, the agent can use `delete_task` to keep the timeline clean.

Setup guide

Set up Ellie Planner 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 Ellie Planner 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="Ellie Planner_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Ellie Planner 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 Ellie Planner. 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 Ellie Planner MCP in Google ADK

Use the McpToolset class pointing to your Vinkius HTTP endpoint. Pass this toolset directly into the tools parameter of your LlmAgent to expose all planner capabilities to Gemini.

The SDK supports both Stdio and HTTP transports. You can run the server locally for development or connect to the managed Vinkius endpoint for production cloud deployments.

Gemini's massive context window easily processes large payloads returned by `list_tasks`. The agent can analyze hundreds of tasks at once without hitting context limits or losing track of dependencies.

Yes, you can use the optional tool names filter in the ADK to restrict exposure. For example, you can block `delete_task` if you want to prevent the agent from removing items.

Yes, your lists, tasks, and labels are processed within your secure Google Cloud perimeter and the Vinkius runtime sandbox. No task details are leaked or used to train public models.

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