How to Use the Miro MCP in LlamaIndex

Q: How do I load Miro board data into a LlamaIndex vector store?

Use BasicMCPClient to connect to the Miro MCP Server, then convert the tools using McpToolSpec. You can run listboarditems to pull sticky notes and load them as Document objects into your index.

Q: Does LlamaIndex support real-time syncing with Miro boards?

You can set up a recurring query in LlamaIndex that calls listboards and updates your vector index whenever a new Miro board is detected.

Q: How do I filter which Miro MCP tools are exposed to LlamaIndex?

Use the allowedtools filter when initializing your LlamaIndex tool spec. This lets you restrict the agent to read-only tools like listboarditems and block destructive actions like deleteboarditem.

Index Miro boards, cards, and sticky notes into LlamaIndex vector stores to build live, searchable canvases.

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Create your Vinkius account to connect Miro 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 with LlamaIndex

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Index Miro Boards with LlamaIndex MCP Server

Turn your visual boards into queryable knowledge. LlamaIndex pulls board data using `get_board` and `list_board_items`, then indexes the sticky notes and cards directly into your vector store. Instead of searching Miro manually, you can query your LlamaIndex RAG pipeline to locate specific architectural decisions or user feedback buried in old boards.

Grounding LlamaIndex Agents with Miro Data

Stop your agents from hallucinating board layouts. By wrapping this MCP Server with `McpToolSpec`, your LlamaIndex agent checks the actual board state using `list_board_items` before generating new content. The agent uses `get_board_item` to get exact coordinates and text, ensuring that any new `create_card` call places elements precisely where they belong.

Synthesizing Miro Comments into Indexes

Keep your knowledge base updated with team discussions. The agent queries `list_comments` across multiple boards, feeding the discussion threads into a LlamaIndex document store. When you query the index about project blockers, LlamaIndex pulls the latest replies from `list_comments` to give you a real-time status update.

Setup guide

Set up Miro 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 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 tools.",
)
response = await agent.run("List recent Miro data")

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Common questions about Miro MCP in LlamaIndex

Use `BasicMCPClient` to connect to the Miro MCP Server, then convert the tools using `McpToolSpec`. You can run `list_board_items` to pull sticky notes and load them as Document objects into your index.

Yes. Your LlamaIndex agent can query an index of project requirements, find missing features, and run `create_card` to add them to your Miro board.

You can set up a recurring query in LlamaIndex that calls `list_boards` and updates your vector index whenever a new Miro board is detected.

Use the `allowed_tools` filter when initializing your LlamaIndex tool spec. This lets you restrict the agent to read-only tools like `list_board_items` and block destructive actions like `delete_board_item`.

Your Miro board contents, comments, and user identities are processed in memory within an ephemeral V8 sandbox. No board data is stored on Vinkius, maintaining a zero-trust execution path.

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