tickadoo
Officialtickadoo® MCPサーバー
tickadoo® MCPサーバーは、Model Context Protocol (MCP) を通じて、AIアシスタントにライブ体験の検索機能を提供します。互換性のあるクライアントから、世界680以上の都市で予約可能な劇場、ショー、ツアー、アトラクション、イベントにアクセスできます。
内部メモ: これは
mcp.tickadoo.comにある公開・エージェント向けMCPであり、Claude、ChatGPT、Cursor、SmitheryなどのMCPクライアントをサポートするインターフェースです。チームの調査用に本番データベースを読み取っていた内部の/mcp-dbエンドポイントは廃止されました。現在は howard リポジトリのdb-investigateClaudeスキルに置き換わっています。tickadooチームのドキュメントで修飾語なしに「MCP」と記載されている場合は、このサーバーを指します。
🌐 言語: ランディングページ対応言語: 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.
Current release: v1.4.2
17個の読み取り専用MCPツール(検索、比較、都市ガイド、家族向け、送迎、現地の旅行のヒントワークフロー)
40以上の言語、681都市にわたる13,090件のプロダクト
ルールベースのオーディエンス+タグの充実(カバー率100%)
正確な日付と価格による空き状況スロット
チェックアウト用ディープリンク+Ghost Checkoutを含む予約契約
ロンドンの劇場30会場のアクセシビリティデータ
両方の検索ツールに完全なエージェントインテリジェンスレイヤーを搭載:
_available_filters(10フィールド: tag_counts, price_range, duration_range, audience, setting, physical, languages, tags, wheelchair, free_cancellation)_conversation_starters(結果データに基づくコンテキストプロンプト)_related_searches(タグベースのフォローアップ提案)_booking_urgency(コンバージョンシグナル: 今日の空き状況、無料キャンセル、評価、車椅子)_cross_sell,_intent_token,_accessibility📊 テキスト応答での結果要約行 + 🔍 フィルターヒント
🔥 テキスト詳細応答での緊急性シグナル
スマートフィルターリカバリー(フィルターが厳しすぎる場合にエージェントをガイド)
機械可読なプロダクトフィードリソース1件
ホスト型MCPクライアント用のリモートHTTPエンドポイント
デスクトップおよび開発ワークフロー用のローカルstdioエントリーポイント
ツール
ツール | 説明 |
| 681都市の13,090件以上の体験を11のフィルター(オーディエンス、設定、車椅子、身体的レベル、期間、言語、評価、キャンセル、価格、タグ、カテゴリー)と6つの並べ替えオプション(best_valueを含む)で検索 |
| 感情的な意図(ロマンチック、リラックス、予算重視、雨の日、冒険的、グルメ)で検索 — 気分をタグ、オーディエンス、評価、設定、価格フィルターにマッピング |
| 緯度/経度付近の体験を同じ11のフィルター、設定可能な半径、日付フィルターで検索 |
| サポートされている都市をオプションのフィルタリングと結果制限付きで閲覧 |
| 特定の体験の高速な日付指定空き状況チェック — 一致するスロット、1人あたりの価格、 |
| スラッグまたは予約パスによる特定のtickadoo体験の詳細な空き状況、価格、会場、画像情報 |
| 2〜5件の体験を並べて比較し、ベストバリュー、最高評価、最も人気、家族向けなどの勝者を提示 |
| 朝/昼/晩の区分がある7日間の都市プランナー |
| 開始時間順および緊急性シグナル付きの今夜の体験 |
| 数時間以内に開始される体験を、開始が早い順に並べ替え |
| キュレーションされた都市の概要:ハイライト、カテゴリーミックス、価格帯、おすすめ、インサイダー情報 |
| 20のローンチ都市向けの現地インサイダーアドバイス:交通、お金、安全、文化、食事、緊急連絡先、簡単なフレーズ |
| 都市のデフォルトの空港、駅、港からホテルの座標までのタクシー、地下鉄/メトロ、バス、電車の送迎見積もり |
| 年齢を考慮したフィルタリングと地理的クラスタリングを備えた家族向けプランナー |
| 特定の体験に対する、意味論的およびヒューリスティックな「おすすめ」結果のブレンド |
すべてのツールは、readOnlyHint、destructiveHint、openWorldHintのMCPツールアノテーションを公開しています。
エージェントインテリジェンスレイヤー
すべての検索応答には、AIエージェント向けに設計されたメタデータキーが含まれています:
キー | 説明 |
| 12フィールド: タグ、オーディエンス、設定、価格帯、期間範囲など |
| 自動キュレーションされたトップ3: ベストバリュー、最高評価、最も人気 |
| 結果価格からの予算/中価格帯/プレミアムのグループ化 |
| タグベースのカテゴリー内訳(例: "8 クルーズ, 6 ガイドツアー, 5 ダイニング") |
| 実際のプロダクトを参照するコンテキスト認識プロンプト |
| 結果を絞り込むためのタグベースの提案 |
| 推奨されるフォローアップアクション |
get_experience_details は以下を追加します: _booking_urgency, _cross_sell, _intent_token, _accessibility
Related MCP server: Nightlife Search
リソース
リソース | 説明 |
| OpenAI Commerce Product Feed形式の機械可読なプロダクトフィード |
接続
ホスト型MCPエンドポイント:
https://mcp.tickadoo.com/mcp
Claude / Cursor
リモートMCP設定の例:
{
"mcpServers": {
"tickadoo": {
"url": "https://mcp.tickadoo.com/mcp"
}
}
}Claude Code
リモートHTTP MCP(推奨 — APIキー不要、ローカルインストール不要):
claude mcp add --transport http tickadoo https://mcp.tickadoo.com/mcpまたはnpmからローカルstdioとして追加:
claude mcp add tickadoo -- npx -y @tickadoo/mcp-serverClaude Code MCPの完全なドキュメントは https://code.claude.com/docs/en/mcp を参照してください。
Claude Dispatch
Claude Dispatchは同じリモートMCP URL設定を使用します:
{
"mcpServers": {
"tickadoo": {
"url": "https://mcp.tickadoo.com/mcp"
}
}
}Gemini CLI
~/.gemini/settings.json に以下を追加:
{
"mcpServers": {
"tickadoo": {
"httpUrl": "https://mcp.tickadoo.com/mcp"
}
}
}Perplexity
Perplexityのカスタムリモートコネクタを使用:
設定 → コネクタ → カスタムコネクタ → リモート
名前:
tickadooMCPサーバーURL:
https://mcp.tickadoo.com/mcpトランスポート:
Streamable HTTP認証:
なしPerplexity有料サブスクライバーが利用可能
ChatGPT
ChatGPT Pro、Business、Enterprise、Eduプランで利用可能:
設定 → アプリとコネクタ → 詳細 → 開発者モードをオン を開く
アプリとコネクタに戻り → 作成
名前:
tickadooURL:
https://mcp.tickadoo.com/mcp認証:
なし新しいチャットで: + → その他 → 開発者モード → ソースを追加 → tickadoo
Android Studio / Firebase Studio
同じ httpUrl 設定が以下で動作します:
Android Studio (
mcp.json)Firebase Studio (
.idx/mcp.jsonまたは.gemini/settings.json)
ローカル開発とStdio
公開後にnpmから実行:
npx -y @tickadoo/mcp-servernpx を介したstdio設定の例:
{
"mcpServers": {
"tickadoo": {
"command": "npx",
"args": ["-y", "@tickadoo/mcp-server"]
}
}
}インストールとビルド:
npm install
npm run buildstdioサーバーを直接実行:
node dist/index.jsstdio設定の例:
{
"mcpServers": {
"tickadoo": {
"command": "node",
"args": ["/path/to/tickadoo-mcp/dist/index.js"]
}
}
}公開リンク
ランディングページ: https://mcp.tickadoo.com
リモートMCPエンドポイント: https://mcp.tickadoo.com/mcp
tickadoo: https://www.tickadoo.com
開発コマンド
コマンド | 目的 |
| esbuildを介してstdioサーバーをバンドル ( |
| ユニットテストスイートを実行 (vitest) |
| ローカルstdioサーバーに対してMCPスモークスイートを実行 |
| HTTPエンドポイントに対してMCPスモークスイートを実行 |
|
|
| メインのMCP Workerをデプロイ ( |
|
|
アーキテクチャ
共有サーバーロジックは src/shared/* に存在します — APIクライアント、フォーマット、ツール定義、リソース登録。トランスポートラッパー:
src/index.ts— ローカルstdioトランスポート (npmで@tickadoo/mcp-serverとして公開)src/worker.ts— Cloudflare Worker (Hono +WebStandardStreamableHTTPServerTransport) がhttps://mcp.tickadoo.comを提供widgets-worker/—https://widgets.tickadoo.comで埋め込み可能なウィジェットを提供する別のCloudflare Worker
デプロイメント
両方のWorkerはCloudflare Workersを介してデプロイされます:
メインMCP worker:
wrangler.jsonc→mcp.tickadoo.comウィジェットworker:
widgets-worker/wrangler.jsonc→widgets.tickadoo.com
CI: .github/workflows/deploy-cf.yml は main へのプッシュごとに実行され、両方のWorkerをデプロイします。
環境変数
変数 | デフォルト | 説明 |
|
| tickadoo APIベースURL |
|
| ログの詳細度: |
|
| tickadooウェブサイトベースURL |
ブランド
tickadoo® は常に小文字です。タグラインは What Do You Wanna Doo?® です。 すべての統合およびドキュメントにおいて小文字を維持してください。
ライセンス
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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