tickadoo
Officialtickadoo® MCP 서버
tickadoo® MCP 서버는 Model Context Protocol(MCP)을 통해 AI 어시스턴트에게 실시간 체험 탐색 기능을 제공합니다. 호환되는 클라이언트를 통해 전 세계 680개 이상의 도시에서 예약 가능한 연극, 쇼, 투어, 관광명소 및 이벤트를 검색할 수 있습니다.
내부 참고: 이 서버는
mcp.tickadoo.com에 위치한 공용 에이전트용 MCP로, Claude, ChatGPT, Cursor, Smithery 및 기타 MCP 클라이언트를 지원합니다. 팀 내부 조사를 위해 프로덕션 데이터베이스를 읽던 별도의 내부/mcp-db엔드포인트는 서비스 종료 후 폐기되었으며, howard 저장소의db-investigateClaude 스킬로 대체되었습니다. tickadoo 팀 문서에서 별도의 수식어 없이 "MCP"라고 언급할 경우 이 서버를 의미합니다.
🌐 언어: 랜딩 페이지 지원 언어: EN · JA · 中文 · 한국어 · DE · FR · ES · IT · PT · tlhIngan Hol 🖖
日本語
tickadoo® MCPサーバーは、AIアシスタント(Claude、ChatGPT、Gemini等)から680以上の都市で13,000以上の体験(劇場、ツアー、アトラクション)を検索できます。APIキー不要、認証不要、即座に接続可能です。
中文
tickadoo® MCP服务器让AI助手(Claude、ChatGPT、Gemini等)可以搜索680+城市中13,000+体验活动(剧院、旅游、景点)。无需API密钥,无需认证,即时连接。
한국어
tickadoo® MCP 서버는 AI 어시스턴트(Claude, ChatGPT, Gemini 등)에서 680+ 도시의 13,000+ 체험(극장, 투어, 관광명소)을 검색할 수 있습니다. API 키나 인증이 필요 없으며 즉시 연결 가능합니다.
현재 릴리스: v1.4.2
검색, 비교, 도시 가이드, 가족 여행, 교통편, 현지 여행 팁 워크플로우를 포함한 17개의 읽기 전용 MCP 도구
40개 이상의 언어로 제공되는 681개 도시의 13,090개 상품
규칙 기반 대상 + 태그 강화 (100% 커버리지)
실제 날짜 및 가격이 포함된 예약 슬롯
결제 딥 링크 + Ghost Checkout을 포함한 예약 계약
런던 연극 공연장 30곳에 대한 접근성 데이터
두 검색 도구 모두에 적용된 전체 에이전트 인텔리전스 레이어:
_available_filters(10개 필드: tag_counts, price_range, duration_range, audience, setting, physical, languages, tags, wheelchair, free_cancellation)_conversation_starters(결과 데이터를 기반으로 한 문맥적 프롬프트)_related_searches(태그 기반 후속 제안)_booking_urgency(전환 신호: 오늘 예약 가능 여부, 무료 취소, 평점, 휠체어 접근성)_cross_sell,_intent_token,_accessibility📊 텍스트 응답 내 결과 요약 라인 + 🔍 필터 힌트
🔥 텍스트 상세 응답 내 긴급성 신호
스마트 필터 복구 (필터가 너무 제한적일 때 에이전트에게 가이드 제공)
기계 판독 가능한 상품 피드 리소스 1개
호스팅된 MCP 클라이언트를 위한 원격 HTTP 엔드포인트
데스크톱 및 개발 워크플로우를 위한 로컬 stdio 진입점
도구
도구 | 설명 |
| 11개 필터(대상, 환경, 휠체어, 신체 활동 수준, 기간, 언어, 평점, 취소, 가격, 태그, 카테고리) 및 6개 정렬 옵션(최고 가치 포함)을 사용하여 681개 도시의 13,090개 이상의 체험 검색 |
| 감정적 의도(낭만적인, 편안한, 가성비 좋은, 비 오는 날, 모험적인, 미식가)에 따라 검색 — 분위기를 태그, 대상, 평점, 환경 및 가격 필터에 매핑 |
| 위도/경도 근처의 체험을 동일한 11개 필터, 구성 가능한 반경 및 날짜 필터링으로 찾기 |
| 선택적 필터링 및 결과 제한을 사용하여 지원되는 도시 탐색 |
| 특정 체험에 대한 빠른 날짜별 예약 가능 여부 확인 — 일치하는 슬롯, 1인당 가격, |
| 슬러그 또는 예약 경로를 통해 특정 tickadoo 체험에 대한 상세 예약 가능 여부, 가격, 장소 및 이미지 정보 확인 |
| 2~5개 체험을 나란히 비교하여 최고 가치, 최고 평점, 가장 인기 있는 항목 및 가족 적합성 추천 |
| 오전/오후/저녁 시간대별로 구분된 7일 도시 플래너 |
| 시작 시간 순위 및 긴급성 신호가 포함된 오늘 밤의 체험 |
| 몇 시간 내에 시작되는 체험을 가장 빠른 순으로 정렬 |
| 큐레이팅된 도시 개요: 주요 하이라이트, 카테고리 구성, 가격 범위, 추천 사항, 내부자 팁 |
| 20개 출시 도시를 위한 현지 내부자 조언: 교통, 돈, 안전, 문화, 음식, 긴급 전화번호, 간단한 문구 |
| 도시의 기본 공항, 역 또는 항구에서 호텔 좌표까지의 택시, 지하철/메트로, 버스 및 기차 이동 예상 정보 |
| 연령별 필터링 및 지리적 클러스터링을 포함한 가족 여행 플래너 |
| 특정 체험에 대해 의미론적 + 휴리스틱 방식이 혼합된 "추천 상품" 결과 |
모든 도구는 readOnlyHint, destructiveHint 및 openWorldHint에 대한 MCP 도구 주석을 노출합니다.
에이전트 인텔리전스 레이어
모든 검색 응답에는 AI 에이전트를 위해 설계된 메타데이터 키가 포함되어 있습니다:
키 | 설명 |
| 12개 필드: 태그, 대상, 환경, 가격 범위, 기간 범위 등 |
| 자동 큐레이팅된 상위 3개: 최고 가치, 최고 평점, 가장 인기 있는 항목 |
| 결과 가격을 기반으로 한 예산/중급/프리미엄 그룹화 |
| 태그 기반 카테고리 분류 (예: "8 크루즈, 6 가이드 투어, 5 다이닝") |
| 실제 상품을 참조하는 문맥 인식 프롬프트 |
| 결과 범위를 좁히기 위한 태그 기반 제안 |
| 권장되는 후속 조치 |
get_experience_details는 다음을 추가합니다: _booking_urgency, _cross_sell, _intent_token, _accessibility
Related MCP server: Nightlife Search
리소스
리소스 | 설명 |
| OpenAI Commerce Product Feed 형식의 기계 판독 가능한 상품 피드 |
연결
호스팅된 MCP 엔드포인트:
https://mcp.tickadoo.com/mcp
Claude / Cursor
원격 MCP 구성 예시:
{
"mcpServers": {
"tickadoo": {
"url": "https://mcp.tickadoo.com/mcp"
}
}
}Claude Code
원격 HTTP MCP (권장 — API 키 필요 없음, 로컬 설치 필요 없음):
claude mcp add --transport http tickadoo https://mcp.tickadoo.com/mcp또는 npm에서 로컬 stdio로 추가:
claude mcp add tickadoo -- npx -y @tickadoo/mcp-server전체 Claude Code MCP 문서는 https://code.claude.com/docs/en/mcp 를 참조하세요.
Claude Dispatch
Claude Dispatch는 동일한 원격 MCP URL 구성을 사용합니다:
{
"mcpServers": {
"tickadoo": {
"url": "https://mcp.tickadoo.com/mcp"
}
}
}Gemini CLI
~/.gemini/settings.json에 다음을 추가하세요:
{
"mcpServers": {
"tickadoo": {
"httpUrl": "https://mcp.tickadoo.com/mcp"
}
}
}Perplexity
Perplexity의 사용자 지정 원격 커넥터를 사용하세요:
설정 → 커넥터 → 사용자 지정 커넥터 → 원격
이름:
tickadooMCP 서버 URL:
https://mcp.tickadoo.com/mcp전송 방식:
Streamable HTTP인증:
없음Perplexity 유료 구독자에게 제공
ChatGPT
ChatGPT Pro, Business, Enterprise 및 Edu 플랜에서 사용 가능:
설정 → 앱 및 커넥터 → 고급 → 개발자 모드 ON을 엽니다.
앱 및 커넥터로 돌아가서 생성을 클릭합니다.
이름:
tickadooURL:
https://mcp.tickadoo.com/mcp인증:
없음새 채팅에서: + → 더 보기 → 개발자 모드 → 소스 추가 → tickadoo
Android Studio / Firebase Studio
동일한 httpUrl 구성이 다음에서 작동합니다:
Android Studio (
mcp.json)Firebase Studio (
.idx/mcp.json또는.gemini/settings.json)
로컬 개발 및 Stdio
게시 후 npm에서 실행:
npx -y @tickadoo/mcp-servernpx를 통한 stdio 구성 예시:
{
"mcpServers": {
"tickadoo": {
"command": "npx",
"args": ["-y", "@tickadoo/mcp-server"]
}
}
}설치 및 빌드:
npm install
npm run buildstdio 서버 직접 실행:
node dist/index.jsstdio 구성 예시:
{
"mcpServers": {
"tickadoo": {
"command": "node",
"args": ["/path/to/tickadoo-mcp/dist/index.js"]
}
}
}게시된 링크
랜딩 페이지: https://mcp.tickadoo.com
원격 MCP 엔드포인트: https://mcp.tickadoo.com/mcp
tickadoo: https://www.tickadoo.com
개발 명령어
명령어 | 목적 |
| esbuild를 통해 stdio 서버( |
| 단위 테스트 모음(vitest) 실행 |
| 로컬 stdio 서버에 대해 MCP 스모크 테스트 모음 실행 |
| HTTP 엔드포인트에 대해 MCP 스모크 테스트 모음 실행 |
|
|
| 메인 MCP Worker 배포 ( |
|
|
아키텍처
공유 서버 로직은 src/shared/*에 위치합니다 — API 클라이언트, 포맷팅, 도구 정의, 리소스 등록. 전송 래퍼:
src/index.ts— 로컬 stdio 전송 (npm에@tickadoo/mcp-server로 게시됨)src/worker.ts—https://mcp.tickadoo.com을 서비스하는 Cloudflare Worker (Hono +WebStandardStreamableHTTPServerTransport)widgets-worker/—https://widgets.tickadoo.com에서 임베드 가능한 위젯을 서비스하는 별도의 Cloudflare Worker
배포
두 Worker 모두 Cloudflare Workers를 통해 배포됩니다:
메인 MCP worker:
wrangler.jsonc→mcp.tickadoo.com위젯 worker:
widgets-worker/wrangler.jsonc→widgets.tickadoo.com
CI: .github/workflows/deploy-cf.yml은 main 브랜치에 푸시될 때마다 실행되어 두 Worker를 모두 배포합니다.
환경 변수
변수 | 기본값 | 설명 |
|
| tickadoo API 기본 URL |
|
| 로깅 상세 수준: |
|
| tickadoo 웹사이트 기본 URL |
브랜드
tickadoo®는 항상 소문자로 표기합니다. 태그라인은 What Do You Wanna Doo?® 입니다. 모든 통합 및 문서에서 소문자 표기를 유지해 주십시오.
라이선스
MIT — tickadoo Inc.
Available Tools
4 toolsfind_nearby_experiencesARead-onlyInspect
Find shows, events and experiences near a geographic location on tickadoo®. Use when a user shares their location or asks for things to do near them.
| Name | Required | Description | Default |
|---|---|---|---|
| latitude | Yes | Latitude | |
| longitude | Yes | Longitude | |
| radius_km | No | Search radius in km (default 25) | |
| language | No | Language code | en |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the agent knows this is a safe, non-destructive query operation. The description adds context about location-based searching but doesn't disclose additional behavioral traits like rate limits, authentication needs, or result format. With annotations covering the core safety profile, a 3 is appropriate as the description provides some useful context without rich behavioral details.
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 two sentences, front-loaded with the core purpose and followed by usage guidance. Every sentence earns its place by providing essential information without redundancy or fluff, making it highly efficient and easy to parse.
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?
Given the tool's moderate complexity (location-based search), rich annotations (read-only, open-world), and full schema coverage, the description is mostly complete. It lacks details on output format (no output schema provided) and doesn't mention pagination or result limits, but the purpose and usage are well-covered, making it adequate for agent selection.
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%, with all parameters (latitude, longitude, radius_km, language) documented in the schema. The description doesn't add meaning beyond the schema, such as explaining coordinate systems or language code specifics. Baseline 3 is correct when the schema fully describes parameters.
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 tool's purpose: 'Find shows, events and experiences near a geographic location on tickadoo®.' It specifies the verb ('Find'), resource ('shows, events and experiences'), and context ('near a geographic location'), distinguishing it from sibling tools like get_experience_details (detail view) and list_cities (city listing).
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?
The description provides explicit usage guidance: 'Use when a user shares their location or asks for things to do near them.' This clearly indicates when to invoke this tool versus alternatives, helping the agent select it based on user context rather than other tools like search_experiences (which might not be location-based).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_experience_detailsARead-onlyInspect
Get detailed availability, venue details, and images for a specific tickadoo® experience. Prefer passing the tickadoo slug or booking URL path; provider and provider_id are legacy fallback inputs.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | No | Preferred: tickadoo slug or path, e.g. 'london-dungeon-tickets' or '/london/london-dungeon-tickets' | |
| provider | No | Legacy fallback only: hidden provider name used internally | |
| provider_id | No | Legacy fallback only: hidden provider-specific product ID | |
| days | No | Number of days of availability to fetch (default 30, max 180) | |
| language | No | Reserved for future language-aware API support | en |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate read-only, non-destructive, and open-world behavior, which the description does not contradict. It adds context by specifying input preferences and the scope of data fetched (availability, venue details, images), enhancing understanding beyond the annotations.
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 front-loaded with the core purpose and usage guidelines in two concise sentences, with no wasted words. Every sentence contributes directly to tool understanding and selection.
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?
Given the tool's complexity (5 parameters, no output schema) and rich annotations, the description is mostly complete. It covers purpose, usage, and input semantics well, but could benefit from mentioning potential outputs or limitations, though annotations help mitigate this gap.
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?
With 100% schema description coverage, the schema fully documents all parameters. The description adds value by clarifying input preferences (slug as preferred, provider/provider_id as legacy fallbacks) but does not provide additional semantic details beyond what the schema already covers.
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 specific action ('Get detailed availability, venue details, and images') and the resource ('a specific tickadoo® experience'), distinguishing it from sibling tools like find_nearby_experiences, list_cities, and search_experiences by focusing on details for a single experience rather than searching or listing.
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?
It provides explicit guidance on when to use this tool by specifying preferred inputs ('tickadoo slug or booking URL path') and fallback options ('provider and provider_id are legacy fallback inputs'), helping the agent choose this over alternatives for retrieving detailed information on a known experience.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_citiesARead-onlyInspect
List all cities where tickadoo® has bookable experiences. Use to help users discover available destinations.
| Name | Required | Description | Default |
|---|---|---|---|
| language | No | Language code | en |
| query | No | Optional city name or slug filter (e.g. 'new', 'paris', 'tokyo') | |
| limit | No | Maximum number of cities to return (default 50) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, covering safety and scope. The description adds minimal behavioral context beyond this, such as the purpose of 'discover available destinations,' but doesn't detail aspects like rate limits, authentication needs, or pagination behavior. It doesn't contradict annotations, so it meets the baseline for having annotations.
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 concise and front-loaded: two sentences that directly state the tool's purpose and usage without unnecessary details. Every sentence earns its place by providing essential information, making it efficient and well-structured.
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?
Given the tool's low complexity (a read-only list operation), rich annotations (covering safety and scope), and 100% schema coverage, the description is mostly complete. It lacks an output schema, but the description doesn't need to explain return values. However, it could be more complete by mentioning potential limitations or result formats, slightly reducing the score.
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%, meaning all parameters are well-documented in the schema itself. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain the 'query' parameter's filtering behavior in more detail). With high schema coverage, the baseline score is 3, as the description doesn't compensate but also doesn't need to.
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 tool's purpose: 'List all cities where tickadoo® has bookable experiences.' It specifies the verb ('List') and resource ('cities'), and distinguishes it from siblings by focusing on destinations rather than experiences. However, it doesn't explicitly differentiate from potential sibling tools like 'search_cities' if they existed, so it's not a perfect 5.
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?
The description provides implied usage context: 'Use to help users discover available destinations.' This suggests it's for discovery purposes, but it doesn't explicitly state when to use this tool versus alternatives like 'search_experiences' or 'find_nearby_experiences' from the sibling list. No exclusions or clear alternatives are mentioned, leaving some ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_experiencesARead-onlyInspect
Search for shows, theatre, events, tours and experiences in a specific city on tickadoo®. Use when a user asks what to do in a city, wants event/show recommendations, or is looking for tickets.
| Name | Required | Description | Default |
|---|---|---|---|
| city | Yes | City name or slug (e.g. 'london', 'new-york', 'paris', 'tokyo', 'dubai') | |
| language | No | Language code (e.g. 'en', 'de', 'fr', 'es') | en |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, so the agent knows this is a safe, read-only search operation with open-world semantics. The description adds useful context about the types of content searched (shows, theatre, events, tours, experiences) and the tickadoo® platform, but doesn't provide additional behavioral details like rate limits, authentication needs, or pagination behavior.
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 perfectly concise and front-loaded: the first sentence states the core functionality, and the second sentence provides clear usage guidelines. Every sentence earns its place with no wasted words or redundant information.
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?
Given that this is a search tool with good annotations (read-only, open-world) and 100% schema coverage, the description provides adequate context about what's being searched and when to use it. However, without an output schema, the description doesn't explain what the search returns (e.g., result format, pagination), leaving a minor gap in completeness.
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%, with both parameters ('city' and 'language') fully documented in the schema. The description doesn't add any parameter-specific semantics beyond what's already in the schema (e.g., it doesn't explain city validation rules or language code formats). With complete schema coverage, the baseline score of 3 is appropriate.
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 specific action ('Search for shows, theatre, events, tours and experiences') and resource ('in a specific city on tickadoo®'), distinguishing it from siblings like 'find_nearby_experiences' (which implies proximity-based search) and 'get_experience_details' (which retrieves specific item details). The verb 'search' is precise and the resource scope is well-defined.
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?
The description explicitly provides when-to-use guidance: 'Use when a user asks what to do in a city, wants event/show recommendations, or is looking for tickets.' This gives clear context for invocation and distinguishes it from alternatives like 'list_cities' (which lists available cities rather than searching within one).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
4 tool updates
v1.1.0- First observed
find_nearby_experiences - First observed
get_experience_details - First observed
list_cities - First observed
search_experiences
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose with no overlap: find_nearby_experiences uses geographic location, get_experience_details retrieves details for a specific experience, list_cities enumerates available destinations, and search_experiences searches within a specific city. The descriptions explicitly differentiate their use cases, eliminating any ambiguity.
All tool names follow a consistent verb_noun pattern (e.g., find_nearby_experiences, get_experience_details, list_cities, search_experiences) with clear, descriptive verbs and nouns. There are no deviations in style or convention, making the set highly predictable and readable.
With 4 tools, the set is well-scoped for a ticketing/experience discovery server, covering key functionalities like location-based finding, detailed lookups, city listing, and city-specific searches. Each tool earns its place without redundancy or excessive complexity.
The tool surface covers core discovery and information retrieval workflows effectively, including location-based and city-specific searches, detailed views, and destination listing. A minor gap exists in booking or transaction capabilities, but agents can work around this for recommendation and exploration tasks.
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