How to Use the Miro (Visual Collaboration & Whiteboarding) MCP in Google ADK

Q: Can I restrict Google ADK to only run specific Miro tools?

Yes. You can pass an optional toolnames filter to the toolset initialization to restrict the agent to read-only tools like listitems and listtags, blocking creation capabilities.

Q: How does Google ADK use the Miro (Visual Collaboration & Whiteboarding) MCP Server to manage workspace tags?

The agent runs listtags to see the current taxonomy, then applies that context when analyzing board elements. This prevents the agent from creating redundant tags and ensures consistent categorization across your enterprise boards.

Deploy enterprise Google ADK agents that translate BigQuery data into Miro boards and visual shapes using Gemini.

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Connect Miro (Visual Collaboration & Whiteboarding) MCP to Google ADK

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Setup Miro (Visual Collaboration & Whiteboarding) with Google ADK

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Google ADK MCP Server Data Visualization

The `create_shape` tool builds geometric structures on your canvas to represent complex data structures visually. Your Gemini agent uses this tool to read database schemas from BigQuery and map them into flowcharts. Because Google ADK supports long-context reasoning with Gemini, the agent can analyze millions of tokens of system documentation before deciding exactly how to structure the shapes.

Automated Board Inventory

The `list_boards` tool lists all active workspaces accessible to your enterprise credentials. Your agent uses this tool to index available canvases and prevent duplicate board creation across teams. This index feeds directly into your Google Cloud infrastructure, allowing you to build automated compliance dashboards that track which teams are actively using their visual workspaces.

Real-Time Content Auditing

The `list_items` tool reads all raw elements placed on a specific canvas. Your agent invokes this tool to extract sticky notes and text blocks, converting them into structured logs for your databases. This lets you archive visual brainstorming sessions automatically. You run the audit script nightly, grab the board state, and store the text in BigQuery without manual copy-pasting.

Setup guide

Set up Miro (Visual Collaboration & Whiteboarding) 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 Miro (Visual Collaboration & Whiteboarding) 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="Miro (Visual Collaboration & Whiteboarding)_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Miro (Visual Collaboration & Whiteboarding) tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Miro (Visual Collaboration & Whiteboarding) MCP in Google ADK

Use the McpToolset class pointing to your Vinkius HTTP endpoint and pass it to your LlmAgent tools parameter. This exposes tools like create_board and create_sticky_note directly to Gemini's tool-calling engine.

Yes. You can pass an optional tool_names filter to the toolset initialization to restrict the agent to read-only tools like list_items and list_tags, blocking creation capabilities.

The agent runs list_tags to see the current taxonomy, then applies that context when analyzing board elements. This prevents the agent from creating redundant tags and ensures consistent categorization across your enterprise boards.

Yes, Google ADK connects to this server over standard HTTP streams hosted on Vinkius, meaning you do not need to manage local node processes or complex network tunneling.

Yes. Your board metadata, shape dimensions, and member lists are transmitted via secure HTTPS directly to the target API. This secure MCP architecture ensures compliance and runs in an ephemeral sandbox.

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