Polyglot AI Board

Read-only: which LLM is best in 7 languages (zh, ko, nb, de, nl, es, pt), from public benchmarks.

我該用這個嗎

品質與安全性

B
說明品質
93%
結構描述完整度
53%
命名品質
100%
汙染風險
100%
權限相符程度
100%
協定合規性
100%

根據工具定義與協定合規性的自動化分析。

上下文成本

~212Token(工具定義)
~203 B典型回應大小
極小的注意力影響(128k 上下文的 0.17%)

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": {
    "board": {
      "url": "https://polyglot-ai-board.vercel.app/api/mcp"
    }
  }
}

遠端端點

https://polyglot-ai-board.vercel.app/api/mcpstreamable-http

它能做什麼

工具清單

工具(3)

🟢 唯讀🟡 寫入🔴 刪除⚪ 未知
🟢list_languages

List the 7 languages covered by the Polyglot AI Board with their codes.

輸入結構描述

{
  "type": "object",
  "properties": {}
}
🟢get_top_pick(lang)

Free: the board's current top LLM pick and best open-weights pick for one language, with the public benchmark source it is based on.

輸入結構描述

{
  "type": "object",
  "properties": {
    "lang": {
      "type": "string",
      "description": "Language code: zh, ko, nb, de, nl, es or pt"
    }
  },
  "required": [
    "lang"
  ]
}
🟢list_products

Paid data packs for agents (model picker, eval suites, false friends, per-language packs) with prices and Vermarco buy links, plus the x402 pay-per-call API.

輸入結構描述

{
  "type": "object",
  "properties": {}
}

社群

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證據

近期觀測

已驗證未記錄版本3 個工具