Parky — Park Planning
Find Disney and Universal rides, posted waits, park hours, and crowd forecasts with Parky.
我該用這個嗎
品質與安全性
根據工具定義與協定合規性的自動化分析。
上下文成本
這是每次將伺服器的工具載入模型上下文時所消耗的約略 token 數量。數量越高，可用於其他工作的注意力就越少。
安裝
一鍵安裝
將以下內容加入你的 `claude_desktop_config.json` 檔案：
{
"mcpServers": {
"parky": {
"url": "https://mcp.parkypass.com/mcp"
}
}
}遠端端點
https://mcp.parkypass.com/mcpstreamable-http它能做什麼
工具清單
工具（4）
🟢parky_find_experience(query, park_id)
Use this when a visitor names or describes a park or ride and you need its canonical Parky ID. Searches only parks in Parky's current Disney and Universal release scope. It does not retrieve current wait times.
輸入結構描述
{
"type": "object",
"properties": {
"query": {
"type": "string",
"minLength": 2,
"maxLength": 100,
"description": "Park or ride name, such as EPCOT or Hagrid's."
},
"park_id": {
"description": "Optional canonical Parky park ID to narrow ride search.",
"type": "string"
}
},
"required": [
"query"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢parky_get_waits(park_id, ride_id)
Use this when a visitor asks for current posted ride waits or operating status at one supported park. Resolve the park ID first. Waits older than 30 minutes are unavailable, not current; this tool does not predict future waits.
輸入結構描述
{
"type": "object",
"properties": {
"park_id": {
"type": "string",
"minLength": 1,
"description": "Canonical Parky park ID from parky_find_experience."
},
"ride_id": {
"description": "Optional canonical ride ID to return one ride only.",
"type": "string"
}
},
"required": [
"park_id"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢parky_get_hours(park_id, date, days)
Use this when a visitor asks about operating hours for one supported park within the next seven park-local days. Resolve the park ID first. Schedule windows have guest-facing categories and labels; Early Entry is an eligibility-based window, not a separate ticketed event. These are reported schedules, which the operator may change.
輸入結構描述
{
"type": "object",
"properties": {
"park_id": {
"type": "string",
"minLength": 1,
"description": "Canonical Parky park ID from parky_find_experience."
},
"date": {
"description": "First date in the park's local time zone, YYYY-MM-DD; defaults to today.",
"type": "string",
"format": "date",
"pattern": "^(?:(?:\\d\\d[2468][048]|\\d\\d[13579][26]|\\d\\d0[48]|[02468][048]00|[13579][26]00)-02-29|\\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\\d|30)|(?:02)-(?:0[1-9]|1\\d|2[0-8])))$"
},
"days": {
"description": "Number of consecutive days, 1 to 7; defaults to 1.",
"type": "integer",
"minimum": 1,
"maximum": 7
}
},
"required": [
"park_id"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢parky_get_crowd_outlook(park_id, date, days)
Use this when a visitor asks how crowded one supported park may be within the next 30 park-local days. Resolve the park ID first. Returns a forecast and range, not a guarantee or a live wait.
輸入結構描述
{
"type": "object",
"properties": {
"park_id": {
"type": "string",
"minLength": 1,
"description": "Canonical Parky park ID from parky_find_experience."
},
"date": {
"description": "First date in the park's local time zone, YYYY-MM-DD; defaults to today.",
"type": "string",
"format": "date",
"pattern": "^(?:(?:\\d\\d[2468][048]|\\d\\d[13579][26]|\\d\\d0[48]|[02468][048]00|[13579][26]00)-02-29|\\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\\d|30)|(?:02)-(?:0[1-9]|1\\d|2[0-8])))$"
},
"days": {
"description": "Number of consecutive days, 1 to 30; defaults to 1.",
"type": "integer",
"minimum": 1,
"maximum": 30
}
},
"required": [
"park_id"
],
"$schema": "http://json-schema.org/draft-07/schema#"
}社群
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