Ticketmaster Discovery API を通じてイベント、会場、アトラクションを検出するためのツールを提供するモデル コンテキスト プロトコル サーバー。
柔軟なフィルタリングを使用して、イベント、会場、アトラクションを検索します。
キーワード検索
イベントの日付範囲
場所（市、州、国）
会場固有の検索
アトラクション固有の検索
イベントの分類/カテゴリ
出力形式:
プログラムで使用するための構造化された JSON データ
人間が直接読めるテキスト
以下を含む包括的なデータ:
名前とID
日時（イベントの場合）
価格帯（イベント用）
URL
画像
場所と住所（会場の場合）
分類（アトラクション）
Related MCP server: Ticketmaster Partner API
npx -y install @delorenj/mcp-server-ticketmasterサーバーにはTicketmaster APIキーが必要です。以下の方法で取得できます。
アカウントの作成またはサインイン
アカウントの「マイアプリ」へ移動
APIキーを取得するための新しいアプリを作成する
MCP 設定ファイルで API キーを設定します。
{
"mcpServers": {
"ticketmaster": {
"command": "npx",
"args": ["-y", "@delorenj/mcp-server-ticketmaster"],
"env": {
"TICKETMASTER_API_KEY": "your-api-key-here"
}
}
}
}サーバーは、次のものを受け入れるsearch_ticketmasterというツールを提供します。
type : 検索の種類（「イベント」、「会場」、「アトラクション」）
keyword : 検索語
startDate : 開始日（YYYY-MM-DD形式、イベントの場合）
endDate : YYYY-MM-DD 形式の終了日 (イベントの場合)
city : 都市名
stateCode : 州コード (例: 'NY')
countryCode : 国コード（例：'US'）
venueId : 特定の会場ID
attractionId : 特定のアトラクションID
classificationName : イベントカテゴリ（例：「スポーツ」、「音楽」）
format : 出力形式（'json' または 'text'、デフォルトは '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>リポジトリをクローンする
サンプル環境ファイルをコピーします。
cp .env.example .envTicketmaster APIキーを.envに追加する
依存関係をインストールします:
npm installプロジェクトをビルドします。
npm run build検査官によるテスト:
npm run inspector貢献を歓迎します！お気軽にプルリクエストを送信してください。大きな変更については、まずIssueを開いて、変更したい点について議論してください。
MITライセンス - 詳細はLICENSEファイルを参照
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.
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