---
title: "Luma Integration for Rig: Query Luma Data in Plain English"
description: "Connect Luma to Rig and query your Luma data in plain English, or ask it in Claude, ChatGPT and Cursor. Governed, validated answers from your warehouse."
canonical: "https://rig.so/integrations/luma"
format: markdown
---

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![Luma logo](https://img.logo.dev/lu.ma?token=pk_AdkTbLWDS1iunmvTK2qm1g&size=112&format=png&retina=true)

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# Luma integration for Rig

## The easiest way to connect Luma to Claude and other AI tools

Luma is an event platform used to run community events, meetups and conferences, handling registration pages, approvals and check-in.

[Try Rig](https://app.rig.so/signup)[Book a demo](https://rig.so/book-demo)

## What Rig syncs from Luma

Once connected, Rig models these objects so questions resolve to the right tables and joins:

- Events
- Guest registrations
- Approval status
- Check-in status
- Registration answers
- Calendar audience
- Person tags
- Coupons

## How Luma connects to Rig

Give Rig an API key for your Luma calendar. Rig syncs events, guest registrations with their approval and check-in status and registration answers, plus the calendar audience, person tags and coupons.

[Read the step-by-step Luma setup guide](https://rig.so/guides/connect-luma)

## Find out whether events produce pipeline

Event attribution usually stops at attendance because the registration list never reaches the CRM. With Luma registrations in the warehouse next to your CRM, attendees can be followed through to opportunities and closed revenue.

Ask Rig

- Which events produced attendees who became customers?
- What is the pipeline value attributable to events this year?
- Do attendees convert faster than other leads?

## Track the registration to attendance gap

Registration numbers flatter every event. Because check-in status comes across with registrations, you can see real show rates by event type, day and audience, and plan capacity on what happens rather than what was promised.

Ask Rig

- What is our average show rate, and how does it vary by event type?
- Which events had the largest gap between registrations and check-ins?
- Does approval-required registration improve attendance?

## Use registration answers as audience data

The questions you ask at registration are often the best first-party data you collect and the least used. In the warehouse those answers become queryable attributes you can segment and follow up on.

Ask Rig

- What roles and company sizes attend our events?
- Which registration answers correlate with becoming a customer?
- What do attendees most often say they want from an event?

## Ask your Luma data in Claude, ChatGPT or Cursor

Rig serves your Luma data to AI assistants over MCP. Once Luma is synced into your warehouse, you can ask questions in plain English from the tool you already use, and every answer is backed by validated, governed SQL.

- [Claude](https://rig.so/integrations/claude)
- [Claude Code](https://rig.so/integrations/claude-code)
- [Cursor](https://rig.so/integrations/cursor)
- [ChatGPT](https://rig.so/integrations/chatgpt)
- [Codex](https://rig.so/integrations/codex)
- [Gemini](https://rig.so/integrations/gemini)

## Frequently asked questions

What does Rig sync from Luma?

Events, guest registrations including approval and check-in status and registration answers, the calendar audience, person tags and coupons.

Can I tell who actually attended rather than registered?

Yes. Check-in status comes across with each registration, which is what makes real show rates measurable.

What do I need to connect Luma?

An API key for the Luma calendar you want to sync.

Can I join attendees to my CRM?

Yes. Once both are in the warehouse, registrations match to contacts and accounts so events can be measured in pipeline rather than in headcount.

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## Connect Luma data to AI tools like Claude

Rig builds a governed context layer over your data so every team, and every AI tool, asks questions and gets answers they can trust.

[Try Rig](https://app.rig.so/signup)[Book a demo](https://rig.so/book-demo)

---

- [This page as HTML](https://rig.so/integrations/luma)
- [Site map for language models](https://rig.so/llms.txt)
- [API and agent documentation](https://rig.so/developers)
