# Ticketmaster MCP Server (`axlymxp/ticketmaster-mcp-server`) Actor

MCP server + scraper for Ticketmaster. Search events, attractions, venues, suggestions and genres live from Claude, ChatGPT, Cursor and other AI agents — or run it as a classic event scraper.

- **URL**: https://apify.com/axlymxp/ticketmaster-mcp-server.md
- **Developed by:** [axly](https://apify.com/axlymxp) (community)
- **Categories:** Integrations, E-commerce, Travel
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event + usage

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Ticketmaster MCP Server

Give your AI assistant **live access to Ticketmaster**. This actor runs as a
**Model Context Protocol (MCP) server**, so agents like **Claude, ChatGPT, Cursor,
and n8n** can search events, attractions and venues, fetch event details,
autocomplete queries and browse the genre taxonomy — on demand, in conversation.

It also runs as a **classic scraper**: a normal run performs a one-shot event
search and pushes rows to a dataset.

Built on Ticketmaster's **official Discovery API backend** (the same one the mobile
app uses), so results are reliable and structured — no CAPTCHAs, no bot-detection
breakage, no API-key setup.

### Who it's for

- **AI builders & agents** — add real-time event/venue data to a chatbot or workflow.
- **Analysts** — ask "what concerts are in Chicago next month under $100?" and get structured answers.
- **App & automation developers** — call the tools from n8n, Make, or custom agents.

### MCP tools

| Tool | What it does |
| --- | --- |
| `search_events` | Search events by keyword, city, country, genre, date window or geo-radius |
| `get_event` | Full detail for a single event by ID |
| `search_attractions` | Find artists, teams and performers (with upcoming-event counts) |
| `search_venues` | Find venues with address, GPS and box-office info |
| `suggest` | Type-ahead across events, attractions and venues |
| `list_classifications` | Browse the segment → genre taxonomy |

Each tool returns clean, structured JSON (name, date, price range, venue + GPS,
lineup, classification, image, URL).

### Connect it

1. Start the actor in **Standby mode** (the Apify Console gives you a Standby URL).
2. Point your MCP client at `<ACTOR_STANDBY_URL>/mcp` (Streamable HTTP transport).
3. Ask your agent to search Ticketmaster — it will call the tools automatically.

Example (Claude Desktop / Cursor MCP config):

```json
{
  "mcpServers": {
    "ticketmaster": {
      "url": "https://<your-standby-url>/mcp"
    }
  }
}
```

### Classic run mode

Run it like any scraper with a simple input to get a dataset of events:

```json
{ "keyword": "Taylor Swift", "countryCode": "US", "maxItems": 50 }
```

### Example tool result (search\_events)

```json
{
  "count": 1,
  "results": [
    {
      "id": "vvG1VZ...",
      "name": "Taylor Swift | The Eras Tour",
      "local_date": "2026-08-16",
      "price_min": 49.5,
      "price_max": 449.5,
      "currency": "USD",
      "genre": "Pop",
      "venue_name": "MetLife Stadium",
      "city": "East Rutherford",
      "url": "https://www.ticketmaster.com/event/..."
    }
  ]
}
```

### FAQ

**What is MCP?** The Model Context Protocol is an open standard that lets AI
assistants call external tools. This actor is an MCP server exposing Ticketmaster
search as tools.

**Do I need a Ticketmaster API key?** No — the actor ships the official app's
consumer key and handles everything.

**How fresh is the data?** Live at call time.

**Can I use it without an AI agent?** Yes — run it as a classic scraper to get a
dataset of events.

**Which markets?** US/Canada, Mexico, Australia, New Zealand, UK and Ireland via
the `market` argument, plus any `country_code` filter.

# Actor input Schema

## `keyword` (type: `string`):

Artist, event, team or venue to search for (classic run mode).

## `market` (type: `string`):

Ticketmaster market host to query.

## `countryCode` (type: `string`):

ISO country filter, e.g. US, GB.

## `maxItems` (type: `integer`):

Max events to return in classic run mode.

## Actor input object example

```json
{
  "keyword": "Taylor Swift",
  "market": "US",
  "countryCode": "US",
  "maxItems": 20
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "keyword": "Taylor Swift"
};

// Run the Actor and wait for it to finish
const run = await client.actor("axlymxp/ticketmaster-mcp-server").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "keyword": "Taylor Swift" }

# Run the Actor and wait for it to finish
run = client.actor("axlymxp/ticketmaster-mcp-server").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "keyword": "Taylor Swift"
}' |
apify call axlymxp/ticketmaster-mcp-server --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=axlymxp/ticketmaster-mcp-server",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/acts/7cTjxGeEQBKgtTTeZ/builds/iXfuwEZ96Bj8SPyuJ/openapi.json