Ticketmaster Discovery API를 통해 이벤트, 장소 및 명소를 검색하는 도구를 제공하는 모델 컨텍스트 프로토콜 서버입니다.
유연한 필터링을 통해 이벤트, 장소 및 명소를 검색하세요.
키워드 검색
이벤트 날짜 범위
위치(도시, 주, 국가)
장소별 검색
명소별 검색
이벤트 분류/카테고리
출력 형식:
프로그래밍 방식으로 사용할 수 있는 구조화된 JSON 데이터
직접 소비할 수 있는 사람이 읽을 수 있는 텍스트
다음을 포함한 포괄적인 데이터:
이름과 ID
날짜 및 시간(이벤트용)
가격 범위(이벤트용)
URL
이미지
위치 및 주소(장소별)
분류(명소별)
Related MCP server: Ticketmaster Partner API
지엑스피1
서버에는 Ticketmaster API 키가 필요합니다. 다음 방법으로 키를 얻을 수 있습니다.
https://developer.ticketmaster.com/ 으로 이동합니다
계정 생성 또는 로그인
계정의 "내 앱"으로 이동
API 키를 얻기 위한 새로운 앱 만들기
MCP 설정 파일에서 API 키를 설정하세요.
{
"mcpServers": {
"ticketmaster": {
"command": "npx",
"args": ["-y", "@delorenj/mcp-server-ticketmaster"],
"env": {
"TICKETMASTER_API_KEY": "your-api-key-here"
}
}
}
}서버는 다음을 허용하는 search_ticketmaster 라는 도구를 제공합니다.
type : 검색 유형('이벤트', '장소', '명소')
keyword : 검색어
startDate : YYYY-MM-DD 형식의 시작 날짜(이벤트의 경우)
endDate : YYYY-MM-DD 형식의 종료 날짜(이벤트의 경우)
city : 도시 이름
stateCode : 주 코드(예: 'NY')
countryCode : 국가 코드(예: 'US')
venueId : 특정 장소 ID
attractionId : 특정 어트랙션 ID
classificationName : 이벤트 카테고리(예: '스포츠', '음악')
format : 출력 형식('json' 또는 'text', 기본값은 'json')
<use_mcp_tool>
<server_name>ticketmaster</server_name>
<tool_name>search_ticketmaster</tool_name>
<arguments>
{
"type": "event",
"keyword": "concert",
"startDate": "2025-02-01",
"endDate": "2025-02-28",
"city": "New York",
"stateCode": "NY"
}
</arguments>
</use_mcp_tool><use_mcp_tool>
<server_name>ticketmaster</server_name>
<tool_name>search_ticketmaster</tool_name>
<arguments>
{
"type": "event",
"keyword": "concert",
"startDate": "2025-02-01",
"endDate": "2025-02-28",
"city": "New York",
"stateCode": "NY",
"format": "text"
}
</arguments>
</use_mcp_tool>저장소를 복제합니다
예제 환경 파일을 복사하세요.
cp .env.example .envTicketmaster API 키를 .env 에 추가하세요.
종속성 설치:
npm install프로젝트를 빌드하세요:
npm run build검사관과 함께 테스트:
npm run inspector기여를 환영합니다! 풀 리퀘스트를 제출해 주세요. 주요 변경 사항의 경우, 먼저 이슈를 열어 변경 사항을 논의해 주세요.
MIT 라이센스 - 자세한 내용은 라이센스 파일을 참조하세요.
Search for events, venues, or attractions on Ticketmaster
| Name | Required | Description | Default |
|---|---|---|---|
| type | Yes | Type of search to perform | |
| keyword | No | Search keyword or term | |
| startDate | No | Start date in YYYY-MM-DD format | |
| endDate | No | End date in YYYY-MM-DD format | |
| city | No | City name | |
| stateCode | No | State code (e.g., NY, CA) | |
| countryCode | No | Country code (e.g., US, CA) | |
| venueId | No | Specific venue ID to search | |
| attractionId | No | Specific attraction ID to search | |
| classificationName | No | Event classification/category (e.g., "Sports", "Music") | |
| format | No | Output format (defaults to json) | json |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but provides minimal behavioral insight. It mentions searching but doesn't disclose rate limits, authentication needs, pagination, error handling, or what happens with partial/no results. This is inadequate for a search tool with 11 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. It earns its place by clearly stating the tool's function in minimal space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a complex search tool with 11 parameters, no annotations, and no output schema, the description is insufficient. It lacks details on behavior, output format (beyond the 'format' parameter), error cases, and usage context, leaving significant gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no additional meaning beyond implying search across multiple resource types, which aligns with the 'type' parameter. Baseline 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Search') and resources ('events, venues, or attractions on Ticketmaster'), making the purpose immediately understandable. It doesn't need to distinguish from siblings since none exist, but it could be more specific about what 'search' entails (e.g., listing vs. filtering).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives or any prerequisites. The description merely states what it does without context about appropriate scenarios, limitations, or integration with other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.2.5search_ticketmasterScored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as searching for events, venues, or attractions, making it straightforward for an agent to understand its function without confusion.
Since there is only one tool, naming consistency is inherently perfect. The tool name 'search_ticketmaster' follows a clear verb_noun pattern, which would be consistent if more tools were added, but as a standalone, it sets a good precedent.
A single tool is too few for a server focused on Ticketmaster events, which typically involves operations like browsing events, getting details, checking availability, or purchasing tickets. This minimal set feels thin and incomplete for the apparent scope, limiting agent capabilities.
The tool surface is severely incomplete for the domain of Ticketmaster events. While search is a useful starting point, there are obvious gaps such as retrieving event details, listing venues, checking ticket availability, or handling bookings, which are essential for comprehensive event management workflows.
Ticketmaster Discovery v2 MCP.
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