How to Use the Miro MCP in Google ADK

Q: Can the agent create nested comment replies?

Yes, by passing a parent comment ID to createcomment, the agent can build threaded conversations directly on specific board elements.

Feed Miro board structures into your Google ADK pipelines to analyze complex visual data with Gemini long-context models.

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Connect Miro MCP to Google ADK

Create your Vinkius account to connect Miro 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 Miro with Google ADK

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Discover enterprise assets via Google ADK

`list_boards` scans your corporate workspace to locate active planning boards and returns their metadata. Your enterprise agent parses this list to find specific project boards, then uses `get_board` to retrieve deep configuration details before running any analytics pipelines. This setup allows Gemini models to ingest entire directory structures. If a board requires a title update to match Google Cloud resource names, `update_board` applies the changes instantly.

Generate canvas layouts with this MCP Server

`list_board_items` extracts every sticky note, card, and shape from the canvas to feed into Gemini's long-context window. The agent processes thousands of layout coordinates at once, identifying bottlenecks in your team's visual workflow. To push updates back to the board, the agent executes `create_sticky_note` or `create_card` to place new tasks at precise coordinates. If the agent detects duplicate or outdated tasks during its analysis, it cleans up the workspace using `delete_board_item`.

Manage Miro workspace access from Gemini agents

`add_board_member` automates onboarding by granting board access to new team members as soon as they join a Google Cloud project directory. The agent verifies permissions with `list_board_members` to ensure only authorized users can edit sensitive canvases. To capture team feedback, the agent uses `list_comments` over the active MCP channel and appends its own system logs using `create_comment`. The agent runs `get_user_context` first to ensure its Google ADK execution context matches the expected Miro user profile.

Setup guide

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

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Common questions about Miro MCP in Google ADK

Instantiate McpToolset using your Vinkius HTTP server parameters and pass it to the LlmAgent constructor. This exposes all 14 board management tools to Gemini's reasoning engine using this MCP Server.

Yes, Gemini's long-context window easily ingests large payloads returned by `list_board_items`. The agent can analyze the entire layout in a single pass to generate structural summaries.

Vinkius handles the OAuth flow externally, giving you a single endpoint token. You pass this token in the server parameters so your agent can execute tools like `create_board` securely.

Yes, by passing a parent comment ID to `create_comment`, the agent can build threaded conversations directly on specific board elements.

Every connection to the Miro API runs through an isolated V8 sandbox on Vinkius. Your board designs, sticky notes, and comments are processed on ephemeral instances that vanish immediately after execution.

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