BoardMix MCP Server for LlamaIndex 10 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add BoardMix as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to BoardMix. "
"You have 10 tools available."
),
)
response = await agent.run(
"What tools are available in BoardMix?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About BoardMix MCP Server
Empower your AI agent to orchestrate your visual collaboration with BoardMix, the leading collaborative whiteboard tool for high-performance teams. By connecting BoardMix to your agent, you transform complex whiteboard navigation and project coordination into a natural conversation. Your agent can instantly list your files, retrieve whiteboard nodes (shapes and sticky notes), audit template libraries, and even browse version history without you ever needing to navigate the complex design workspace. Whether you are managing a brainstorming session or a detailed project roadmap, your agent acts as a real-time visual assistant, keeping your assets organized and your team aligned.
LlamaIndex agents combine BoardMix tool responses with indexed documents for comprehensive, grounded answers. Connect 10 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- File Orchestration — List all accessible whiteboards and design files across your BoardMix workspace.
- Node Management — Retrieve granular whiteboard nodes and shapes to understand your visual layout instantly.
- Team Coordination — Browse teams and projects to manage collaboration and assignments effectively.
- Collaboration Monitoring — List whiteboard comments and organization members to stay informed about team updates.
- Template Auditing — Browse available design templates to kickstart new collaborative sessions.
- Version Control — Check the version history of whiteboard files to track changes and milestones.
The BoardMix MCP Server exposes 10 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect BoardMix to LlamaIndex via MCP
Follow these steps to integrate the BoardMix MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 10 tools from BoardMix
Why Use LlamaIndex with the BoardMix MCP Server
LlamaIndex provides unique advantages when paired with BoardMix through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine BoardMix tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain BoardMix tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query BoardMix, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what BoardMix tools were called, what data was returned, and how it influenced the final answer
BoardMix + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the BoardMix MCP Server delivers measurable value.
Hybrid search: combine BoardMix real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query BoardMix to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying BoardMix for fresh data
Analytical workflows: chain BoardMix queries with LlamaIndex's data connectors to build multi-source analytical reports
BoardMix MCP Tools for LlamaIndex (10)
These 10 tools become available when you connect BoardMix to LlamaIndex via MCP:
create_file
Create a new whiteboard
get_comments
Get whiteboard comments
get_file
Get whiteboard file details
get_file_versions
Get file version history
get_org_info
Get organization details
list_files
List all BoardMix files
list_nodes
List whiteboard nodes
list_team_projects
List team projects
list_teams
List available teams
list_templates
List whiteboard templates
Example Prompts for BoardMix in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with BoardMix immediately.
"List all whiteboards in my BoardMix workspace."
"Show me the comments for whiteboard 'board-8821'."
"Retrieve the nodes for whiteboard 'architecture-layout'."
Troubleshooting BoardMix MCP Server with LlamaIndex
Common issues when connecting BoardMix to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpBoardMix + LlamaIndex FAQ
Common questions about integrating BoardMix MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect BoardMix with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect BoardMix to LlamaIndex
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.