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

Q: Can LlamaIndex query specific Miro (Visual Collaboration & Whiteboarding) boards?

Yes. The agent uses the listboards tool to find the correct board ID, then calls getboard to extract the metadata needed to target its search.

Q: How do I limit which tools the agent can access?

You can use the allowedtools filter when setting up your McpToolSpec. This lets you restrict the agent to read-only tools like listitems if you want to prevent automated board creation.

Index Miro boards directly into your LlamaIndex vector stores to ground your RAG applications in real-time visual data.

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Connect Miro (Visual Collaboration & Whiteboarding) MCP to LlamaIndex

Create your Vinkius account to connect Miro (Visual Collaboration & Whiteboarding) to LlamaIndex 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 (Visual Collaboration & Whiteboarding) with LlamaIndex

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Index Canvas Data with LlamaIndex

The Miro MCP Server lets LlamaIndex pull raw data from your canvas using `list_items` and `list_tags`. This workflow converts your visual boards into searchable vector nodes. Your agent can then query past brainstorming sessions. Instead of hallucinating, your RAG pipeline answers questions using actual text extracted from your sticky notes and shapes.

Build Boards From Search Queries

The Miro MCP Server allows your LlamaIndex agent to build visual summaries automatically by executing `create_board`. It establishes a clean workspace based on search results. The agent then populates the workspace by calling `create_sticky_note` for each key insight. This turns dense search results into an organized, collaborative layout that your team can immediately work with.

Map Visual Layouts to Structured Indices

The Miro MCP Server provides `get_board` so your LlamaIndex pipeline can read the high-level metadata of your workspace. Visual layouts hold structure that text files lack. The agent can then use `create_shape` to group related concepts or run `list_members` to track who contributed. It links physical board geometry directly to your semantic index.

Setup guide

Set up Miro (Visual Collaboration & Whiteboarding) MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Miro (Visual Collaboration & Whiteboarding) MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Miro (Visual Collaboration & Whiteboarding) tools.",
)
response = await agent.run("List recent Miro (Visual Collaboration & Whiteboarding) data")

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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 Miro. 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 Miro (Visual Collaboration & Whiteboarding) MCP in LlamaIndex

Use the llama-index-tools-mcp package to initialize the MCP client. You can then convert the `list_items` tool into a query engine tool that LlamaIndex indexes dynamically.

Yes. The agent uses the `list_boards` tool to find the correct board ID, then calls `get_board` to extract the metadata needed to target its search.

Yes, you can register the MCP tools with a LlamaIndex Workflow. This lets you build event-driven pipelines that trigger `create_sticky_note` when new data enters your vector store.

You can use the allowed_tools filter when setting up your McpToolSpec. This lets you restrict the agent to read-only tools like `list_items` if you want to prevent automated board creation.

Your board metadata, sticky note text, and shape coordinates are never stored by Vinkius. The server operates in a zero-trust environment, passing your Miro API tokens and board contents directly to your local LlamaIndex environment.

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