Words in Context

com.gumballtools由 gumballtools.com 發布官方發布者v0.1.0更新於 Oct 24, 2026

Words-in-context vocabulary practice questions with distractor explanations.

發布方自己的服務:Amortization Schedule

已驗證Streamable HTTP可網頁執行

概覽

AI 產生的概覽

讓助理出字彙填空練習題、核對答案並解釋每個選項,也能依學習者提供的文章出題。

可以做什麼
提供字彙填空練習題:draw_items 從人工撰寫的題庫抽出題目,回應刻意不含答案;check_answer 核對作答並回傳教學內容,包括正確選項為何符合句意、所選選項為何不對,以及每個干擾選項錯誤的原因;generate_items 可依學習者提供的文章產生新題目。
適用情境
適合語言學習者或家教,用來做字彙填空練習、複習答錯的題目,或針對學習者自己的閱讀材料出題。若只需要現成題庫,用免費的 draw_items 即可。
執行需求
遠端 MCP 端點,透過串流 HTTP 連線,不需在本機安裝套件;未宣告任何驗證、環境變數或標頭。generate_items 為付費功能。
安裝前請注意
generate_items 是付費層級,每次呼叫都會實際收費,非必要應改用免費的 draw_items。使用 generate_items 時,學習者提供的文章內容會傳送給第三方服務。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Words in Context,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/com.gumballtools%2Fwords-in-context/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。

{
  "mcpServers": {
    "words-in-context": {
      "type": "http",
      "url": "https://words-in-context.gumballtools.com/api/mcp"
    }
  }
}

README

該儲存庫沒有 README。

工具

3

draw_items

Draw practice questions

Draw words-in-context vocabulary practice questions from a curated, human-written bank. Use this to quiz a learner, build a practice set, or check what a question of this type looks like. It is free, deterministic, and costs no inference. IMPORTANT: the response deliberately contains NO answer index and NO explanations. That is so you can present the questions without leaking the answers. Call `check_answer` with the item id and the chosen option to get the answer, why it fits, and why each distractor fails. Input: `count` (1-20, default 5) — an out-of-range count is REFUSED rather than clamped, so you learn the limit. `difficulty` is foundation|core|stretch. `theme` is science|humanities|social-science|literature. `seed` makes the draw reproducible: the same seed always returns the same items, so a practice session can be replayed or shared. Format note: these test inference from context, which is how the current digital SAT asks about vocabulary — not recall of definitions. Each item is a sentence with one word blanked and four options.

輸入參數seedcountthemedifficulty

check_answer

Check an answer

Check an answer to a practice item and get the teaching content. Returns whether the choice was correct, which option was right, why it fits the sentence specifically, why the chosen option was wrong, and the reason EVERY distractor fails. Read the distractor reasons out to the learner even when they answered correctly. Knowing why the tempting wrong answer was tempting is the part that transfers to the next question; being told "correct" teaches nothing. Input: `id` from a draw response, and `choice` as the zero-based index of the selected option.

輸入參數id必填choice必填

generate_items

Generate practice questions from a passage

Generate new practice items from a passage the learner supplies — their own reading, or the material they got wrong. This is the PAID tier and it costs real money per call, unlike the curated bank. Prefer `draw_items` unless the learner specifically needs questions from their own material. `model` is a priced choice: "economy" at $0.002 per item (Fast and cheap. Good enough for straightforward vocabulary in clear prose.); "standard" at $0.008 per item (Better at writing distractors that are genuinely tempting, which is the hard part of a good practice item.). Pick economy for straightforward prose and standard when the distractors need to be genuinely tempting, which is the hard part of a good question. Limits: passage 200 characters minimum, and `count` at most 5 per call. Generation is capped at 10 calls per caller per day, separately from the free quota. Generated items are NOT reviewed by a person. Every response carries a caveat saying so. Check the answer and the distractor reasons before giving them to a learner — a generated question with two defensible answers is worse than no question. Returns 503 when generation is not enabled on the deployment; fall back to `draw_items`.

輸入參數countmodelsource必填difficulty

版本歷史

1
  1. v0.1.0最新Sep 16, 2026

評分

已滿足適用檢查項的 75%

該評分衡量此收錄條目的完整程度,依據註冊中心條目、端點與公開來源計算得出。它不是對伺服器本身的評價,也不表示伺服器安全或目前可用:可連通性是帶日期的檢查結果,評分也不包含安裝量或使用者評價。

  • 近 30 天內可連通必需25 分
  • 已宣告認證方式必需10 分
  • 已列出工具必需15 分
  • 描述必需15 分
  • 圖示10 分
  • 文件15 分

    請宣告包含 README 的 GitHub 儲存庫,或在 OAuth 受保護資源後設資料中提供 resource_documentation。

  • 授權條款10 分

    請在儲存庫或註冊中心條目中宣告授權條款。

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