SpinGras
EU AI Act Article 4 (AI literacy) readiness check and intro booking with SpinGras, Amsterdam.
我該用這個嗎
品質與安全性
A
發現項目(1)
- LOW在 list_services 中
根據工具定義與協定合規性的自動化分析。
上下文成本
~1,057Token(工具定義)
~1.9 KB典型回應大小
中等的注意力影響(128k 上下文的 0.83%)
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": {
"mcp": {
"url": "https://mcp.spingras.io/mcp"
}
}
}遠端端點
https://mcp.spingras.io/mcpstreamable-http它能做什麼
工具清單
工具(4)
🟢 唯讀🟡 寫入🔴 刪除⚪ 未知
🟢list_services
Company facts and the four ways to work with SpinGras: workshop, 90-day rollout, keynote, retainer.
輸入結構描述
{
"type": "object",
"properties": {},
"$schema": "https://json-schema.org/draft/2020-12/schema"
}🟢assess_article4_readiness(usesAi, staffUsingAi, hasAiUsePolicy, trainingDelivered, trainingRecorded, ...)
Checks an organisation's AI literacy measures against Article 4 of the EU AI Act and returns prioritised gaps with sources. Deterministic, not legal advice.
輸入結構描述
{
"type": "object",
"properties": {
"usesAi": {
"type": "boolean",
"description": "Does anyone in the organisation use AI tools (e.g. ChatGPT, Copilot) or AI systems for work?"
},
"staffUsingAi": {
"type": "integer",
"minimum": 0,
"maximum": 1000000,
"description": "Approximate number of staff using AI for work"
},
"hasAiUsePolicy": {
"type": "boolean",
"description": "Is there written guidance on which AI tools may be used and for what?"
},
"trainingDelivered": {
"type": "boolean",
"description": "Have staff who use AI received any AI literacy training or guidance?"
},
"trainingRecorded": {
"type": "boolean",
"description": "Is that training documented (who, when, what)?"
},
"trainingRoleSpecific": {
"type": "boolean",
"description": "Is training matched to roles and the AI systems each role uses?"
},
"sensitiveUseCases": {
"type": "boolean",
"description": "Is AI used for decisions about people (hiring, credit, customers' eligibility) or with sensitive data?"
}
},
"required": [
"usesAi",
"staffUsingAi",
"hasAiUsePolicy",
"trainingDelivered",
"trainingRecorded",
"trainingRoleSpecific",
"sensitiveUseCases"
],
"$schema": "https://json-schema.org/draft/2020-12/schema"
}🟢get_intro_slots(from, days, timeZone)
Returns open 30-minute intro call slots with SpinGras, grouped by date.
輸入結構描述
{
"type": "object",
"properties": {
"from": {
"description": "First date to check, 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])))$"
},
"days": {
"default": 7,
"type": "integer",
"minimum": 1,
"maximum": 14
},
"timeZone": {
"default": "Europe/Amsterdam",
"description": "IANA time zone for returned times",
"type": "string",
"maxLength": 64,
"pattern": "^[A-Za-z_]+(\\/[A-Za-z0-9_+-]+){0,2}$|^UTC$"
}
},
"$schema": "https://json-schema.org/draft/2020-12/schema"
}🟢request_intro(name, email, company, topic, date)
Builds a prefilled booking link for a 30-minute intro call. Does not book anything: give the link to the user to confirm a time themselves.
輸入結構描述
{
"type": "object",
"properties": {
"name": {
"type": "string",
"minLength": 1,
"maxLength": 100
},
"email": {
"type": "string",
"maxLength": 254,
"format": "email",
"pattern": "^(?:[A-Za-z0-9_'+\\-]+\\.)*[A-Za-z0-9_'+\\-]*[A-Za-z0-9_+-]@(?:[A-Za-z0-9][A-Za-z0-9\\-]*\\.)+[A-Za-z]{2,}$"
},
"company": {
"type": "string",
"maxLength": 100
},
"topic": {
"description": "What the user wants to discuss",
"type": "string",
"maxLength": 500
},
"date": {
"description": "Preferred date, YYYY-MM-DD",
"type": "string",
"format": "date",
"pattern": "^(?:(?:\\d\\d[2468][048]|\\d\\d[13579][26]|\\d\\d0[48]|[02468][048]00|[13579][26]00)-02-29|\\d{4}-(?:(?:0[13578]|1[02])-(?:0[1-9]|[12]\\d|3[01])|(?:0[469]|11)-(?:0[1-9]|[12]\\d|30)|(?:02)-(?:0[1-9]|1\\d|2[0-8])))$"
}
},
"$schema": "https://json-schema.org/draft/2020-12/schema"
}社群
證據
近期觀測
已驗證未記錄版本4 個工具