How to Use the BoardMix MCP in LlamaIndex

Q: Can I search BoardMix comments in LlamaIndex?

You can use the getcomments tool to pull discussion history into your index. This allows your LlamaIndex agent to provide context based on team feedback left on your designs.

Index your BoardMix whiteboard data into LlamaIndex for intelligent search and retrieval.

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Connect BoardMix MCP to LlamaIndex

Create your Vinkius account to connect BoardMix 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 BoardMix with LlamaIndex

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Query your BoardMix files using LlamaIndex

This MCP Server allows LlamaIndex to pull metadata from your whiteboards and index it for vector search. You can ask questions about file contents or team structures and get answers grounded in your actual BoardMix data. By using `list_files` and `get_file`, your agent builds a searchable knowledge base of your visual projects. It avoids hallucinations by relying on the live API responses from your account.

Build RAG apps with BoardMix and LlamaIndex

Combine your whiteboard documentation with other internal documents into a single index. The agent uses `list_nodes` to understand the layout and content of your diagrams before answering user queries. This setup creates a unified view of your project information. You can search across your entire BoardMix organization and other data sources simultaneously.

Filter BoardMix tools for secure LlamaIndex access

You can restrict which BoardMix tools are available to your agent using the allowed_tools filter. This ensures your LlamaIndex application only accesses the specific whiteboard data you permit. Setting `include_resources=True` allows the agent to ingest more granular data types from your boards. It keeps your agent focused on the relevant parts of your workflow.

Setup guide

Set up BoardMix 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 BoardMix 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 BoardMix tools.",
)
response = await agent.run("List recent BoardMix 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 BoardMix. 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 BoardMix MCP in LlamaIndex

Install the llama-index-tools-mcp package and initialize a BasicMCPClient with your endpoint. Then, convert the BoardMix functions into tool specs for your FunctionAgent.

LlamaIndex creates an internal vector index of the data pulled from BoardMix. It does not store your actual whiteboard images or proprietary assets permanently.

You can use the get_comments tool to pull discussion history into your index. This allows your LlamaIndex agent to provide context based on team feedback left on your designs.

The server only processes whiteboard metadata and node information that you explicitly request. Your data is never shared with other Vinkius users.

The server converts tool results into a format that LlamaIndex can ingest into its vector store. This turns raw API data into searchable knowledge.

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