Luma MCP Server for LlamaIndexGive LlamaIndex instant access to 6 tools to Add Guests To Event, Create Event, List Calendar Subscribers, and more
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Luma as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
Ask AI about this App Connector for LlamaIndex
The Luma app connector for LlamaIndex is a standout in the Industry Titans category — giving your AI agent 6 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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 Luma. "
"You have 6 tools available."
),
)
response = await agent.run(
"What tools are available in Luma?"
)
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 Luma MCP Server
Connect your Luma (lu.ma) account to any AI agent and take full control of your event orchestration and community engagement through natural conversation. Luma provides a robust platform for managing calendars and events, and this integration allows you to retrieve event metadata, manage guest lists, and create new activities directly from your chat interface.
LlamaIndex agents combine Luma tool responses with indexed documents for comprehensive, grounded answers. Connect 6 tools through 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
- Event & Calendar Orchestration — List all managed events and retrieve detailed metadata programmatically to ensure your community roadmap is always synchronized.
- Guest Lifecycle Management — Access and monitor guest lists and add new attendees directly from the AI interface to maintain high-fidelity event engagement.
- Communication & Update Control — List hosts and organizers linked to a calendar via natural language to drive better team alignment.
- Organization Oversight — Access organizational events and monitor system webhooks using simple AI commands.
- Operational Monitoring — Track system responses and manage event metadata to ensure your community workflows are always optimized.
The Luma MCP Server exposes 6 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.
All 6 Luma tools available for LlamaIndex
When LlamaIndex connects to Luma through Vinkius, your AI agent gets direct access to every tool listed below — spanning event-registration, community-engagement, attendee-management, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Manually add guests to an event
Create a new Luma event
List subscribers to your calendar
List guests for an event
List your Luma events
List all events in your organization
Connect Luma to LlamaIndex via MCP
Follow these steps to wire Luma into LlamaIndex. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
pip install llama-index-tools-mcp llama-index-llms-openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the agent
agent.py and run: python agent.pyExplore tools
Why Use LlamaIndex with the Luma MCP Server
LlamaIndex provides unique advantages when paired with Luma through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Luma tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Luma tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Luma, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Luma tools were called, what data was returned, and how it influenced the final answer
Luma + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Luma MCP Server delivers measurable value.
Hybrid search: combine Luma real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Luma 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 Luma for fresh data
Analytical workflows: chain Luma queries with LlamaIndex's data connectors to build multi-source analytical reports
Example Prompts for Luma in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Luma immediately.
"List all my upcoming events in Luma."
"Show me the guest list for the 'Product Launch' event."
"Add 'sarah@example.com' to the workshop guest list."
Troubleshooting Luma MCP Server with LlamaIndex
Common issues when connecting Luma to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpLuma + LlamaIndex FAQ
Common questions about integrating Luma MCP Server with LlamaIndex.