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How to Use the Hub Planner MCP in Google ADK

Sync your Hub Planner data into Google ADK agents to build enterprise-grade resource planning tools on Google Cloud.

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…and any MCP-compatible client

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Google ADK

Connect Hub Planner MCP to Google ADK

Create your Vinkius account to connect Hub 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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Resource availability in Google ADK

Your agent gains direct visibility into your staffing levels. It executes `list_resources` and `list_unassigned` to find the right person for a task. Data stays local to the agent's context. This allows for complex reasoning across your entire resource pool without leaving the Google Cloud environment.

Project visibility for Google ADK agents

Bring your project list into the agent's reasoning loop. By calling `list_projects` and `list_categories`, your agent categorizes work based on live status. It makes smarter assignments. The agent uses these inputs to determine project urgency against real-time team capacity.

Event and client data access

Your agent tracks client requirements against team availability. It fetches `list_clients` and `list_events` to ensure project kickoffs align with client constraints. This prevents scheduling oversights. The agent uses the returned data to validate that no project overlaps with scheduled time-off.

Setup guide

Set up Hub 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. 1

    Install Google ADK

    Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.

  2. 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. 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. 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 Hub 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="Hub Planner_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Hub Planner tools via MCP.",
    tools=mcp_tools,
)

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

Why Choose Vinkius

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Real-time monitoring

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

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Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Hub Planner MCP in Google ADK

Use the McpToolset provided by the framework. Pass your server parameters to the StreamableHttpServerParameters class to link the Hub Planner tools.
Yes, you can use the tool_names filter to restrict which functions your agent can call. This ensures your agent only interacts with specific tools like `list_resources`.
The Gemini models used by the framework handle large context windows well. Your agent can digest entire lists of `list_bookings` to identify complex scheduling patterns.
The integration uses secure HTTP transports for all communication. You control the endpoint and authentication, keeping your resource data isolated within your infrastructure.
The server treats your resource and booking records as private. Only the data explicitly returned by the API is processed by your agent, ensuring that sensitive information is not logged or exposed.

Start using the Hub Planner MCP today

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