MCP server for Luma event discovery — search by category, city, distance, and keywords with calendar export
Project description
Luma Events MCP Server
A FastMCP server that discovers events from Luma — combining the Discover feed and subscribed calendars — with distance filtering and ICS export. No API key required for basic discovery.
How it works
Luma's Discover API has two endpoints that behave very differently:
- Category search (e.g. AI, Tech, Food) — returns hundreds of events with rich tagging, but only for your home region. Great depth, geographically locked.
- City search (e.g. Paris, London, Tokyo) — returns a curated set of ~20–40 top/featured events for that city. Broad coverage, smaller set.
This MCP uses both via two search modes:
- Home mode (default, no
cityparam) — searches your preferred categories via the Category API. Deep, rich results filtered by your stored address and distance. - Travel mode (pass a
city) — fetches the curated top events for that city via the Place API.
On first run, the server returns popular events near you (geo-biased by IP), then walks you through setting up categories, address, and login for progressively richer results.
Tools
| Tool | What it does |
|---|---|
search_events |
Home mode: search by category with address/distance filtering. Travel mode: curated events for a specific city. |
set_preferences |
Save default categories (list), address, and distance. Persists in SQLite across restarts. |
get_event |
Fetch full details for a single event by API id or lu.ma URL. |
export_event_ics |
Generate an ICS string for any event — paste into Apple Calendar, Google Calendar, Outlook, etc. |
Setup
Prerequisites
- Python 3.10+
- uv (recommended) or pip
Install
git clone <this-repo>
cd "Luma Cal MCP"
uv venv .venv --python 3.12
source .venv/bin/activate
uv pip install -e .
Subscribed calendars (optional)
To access events from calendars you follow on Luma, install the optional auth dependencies:
uv pip install -e ".[auth]"
playwright install chromium
First run
On first use, the raw Discover feed returns hundreds of popular events near you (geo-biased by IP). The server then walks you through setup one prompt at a time to narrow results:
- Address — asks for your location and preferred search radius, which dramatically reduces the result set to events near you.
- Categories — asks which topics interest you (from: tech, ai, food, arts, climate, fitness, wellness, crypto) for focused discovery.
- Login — asks whether to log in for subscribed calendars.
Each prompt appears after returning results, so you see events immediately. After you configure a preference, the search reruns automatically and the next prompt appears. You can respond "not now" (prompt reappears next time) or "never" (permanently dismissed).
Configure
Use set_preferences to save defaults that persist across restarts:
set_preferences(address="3180 18th St, San Francisco", max_distance_miles=15)
set_preferences(categories=["ai", "tech"])
Run
# stdio transport (for Cursor, Claude Desktop, etc.)
fastmcp run src/luma_mcp/server.py
# or directly
python -m luma_mcp.server
Authentication
Subscribed calendars require a Luma session cookie. The server handles this automatically via an inline login flow.
How it works:
- First call — after results, the server prompts for login. The agent asks you in chat.
- Login — the agent calls
search_eventswithlogin=true. A Chromium browser opens tolu.ma/signin; log in normally. The session cookie is stored in the local SQLite DB. - Decline — the agent calls
search_eventswithskip_login_days=Nto defer (0 = ask next time, -1 = never). - Returning user, cookie expired — the browser opens automatically for re-authentication.
- Validation — the stored cookie is validated against Luma's API every 24 hours.
New Event Tracking
The server maintains a local SQLite database (~/.luma-mcp/events.db by default) that records the first time each event is seen. This enables two filters on search_events:
added_within_days— only return events first seen within the last N days.new_only— only return events that have never been seen before.
Every result also includes first_seen_at (ISO timestamp) and is_new (boolean).
Cursor MCP Configuration
Add to your Cursor MCP settings (.cursor/mcp.json):
{
"mcpServers": {
"luma-events": {
"command": "uv",
"args": [
"run",
"--directory", "/path/to/Luma Cal MCP",
"fastmcp", "run", "src/luma_mcp/server.py"
],
"env": {
"PYTHONPATH": "/path/to/Luma Cal MCP/src"
}
}
}
}
Data Sources
| Source | Auth | Coverage |
|---|---|---|
Discover (api.lu.ma) |
None required | Public events by city and category — same feed as luma.com/discover |
Subscribed calendars (api.lu.ma) |
Browser login (auto-managed) | Events from calendars you follow on Luma |
Without logging in, the server still works — Discover is fully available with no authentication.
Distance Filtering
Set a home address via set_preferences(address="...") with max_distance_miles. In home mode, events beyond the radius are excluded. Events without location data are included by default (with distance_miles: null). In travel mode, distance filtering uses the city center at 25 miles automatically.
Geocoding uses Nominatim (free, OpenStreetMap) by default. For higher volume, set GEOCODING_PROVIDER=google or mapbox with the corresponding GEOCODING_API_KEY in your environment.
Event Times
Event times (start_at, end_at) are returned in the user's system timezone. The timezone field from Luma is included in every result for reference.
Limitations
- RSVP is browser-only.
get_eventreturns the RSVP URL; there's no headless registration path. Useexport_event_icsto add events to your calendar. - Web endpoints are undocumented. The Discover and subscribed-calendars feeds use Luma's internal API (
api.lu.ma), which can change without notice. Breakage is isolated toluma_web_client.py.
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