Memora MCP
Memora MCP
将任何对话变成交互式学习会话,直接在 Claude Desktop 中进行。让 Claude 制作一副牌组,它会生成卡片,然后将其渲染为可点击浏览的内联复习界面:翻转闪卡、回答选择题、填写完形填空空白处。每次作答都会更新间隔重复计划,你的结果会回流给 Claude,以便它针对你答错的内容进行强化练习。
关键词:Model Context Protocol、MCP server、MCP Apps、Claude Desktop、闪卡、测验、间隔重复、SRS、FSRS、Anki 替代品。
基于 MCP Apps 扩展(SEP-1865)构建:核心 MCP 规范 2025-11-25 加上 Apps 扩展 2026-01-26。
功能
三种学习方式,全部内联渲染,且评分方式相同:
闪卡:点击翻转,然后评分记住了 / 没记住。
选择题测验:选择一个选项,正确/错误答案会立即显示。
完形填空:空白处原位揭示,句子保持完整。在卡片正面将空白写成
[...],它就会自动变成完形填空卡片。
间隔重复:每次评分都会更新每张卡片的 FSRS 计划(通过 ts-fsrs),因此薄弱卡片会更早重现,到期卡片优先出现。询问 "今天有什么到期的?" 即可获得所有牌组的汇总。
用分类组织:用 :: 命名牌组以嵌套它们(例如 LLM::Attention)。浏览分类树,或将同一棵树作为交互式思维导图浏览,并在一个合并会话中学习整个分支。测验牌组会带有徽章标记。
管理你的牌组:无需离开聊天即可创建、追加、编辑、重命名和删除牌组与卡片。创建牌组时传入 reverse 还可以对每张卡片进行反向练习(对词汇学习很方便)。
纯 JSON:牌组存放在 data/decks.json 中,每次调用时实时读取。可以手动编辑,也可以让 Claude 来构建。无需数据库,无需外部服务。
Related MCP server: EduChain MCP Server
工具
只有 review_deck 和 study 会打开内联翻卡界面;其他工具都返回文本摘要,因此在聊天中编辑或创建不再弹出该组件。
工具 | 用途 |
| 打开一副牌组进行复习(到期卡片优先,每次会话有数量上限)。 |
| 复习整个分类子树,合并到一个会话中(每次会话有数量上限)。 |
| 生成闪卡或完形填空卡片; |
| 生成选择题。 |
| 记录复习结果并更新卡片的 FSRS 计划(由界面调用)。 |
| 汇总所有牌组中到期的内容,并标记掌握不佳的卡片(遗忘 3 次及以上)。 |
| 修改卡片的正面和/或背面。 |
| 建议将卡片拆分为原子化的小卡片,或重写以测试理解程度。 |
| 在用户批准建议的卡片后持久化改进结果。 |
| 将刚刚让你受挫的内容(一个 bug、一道答错的题)转化为草稿卡片。 |
| 在用户批准后持久化捕获的卡片。 |
| 重命名牌组(同时会在分类树中移动它)。 |
| 删除单张卡片。 |
| 删除整个牌组。 |
卡片生成遵循 Memora 的质量规则(原子化的单一概念卡片、1-5 个词的答案、主动回忆、无歧义、不泄露答案、应用优先于定义),基于 Wozniak 的 《知识表述的 20 条规则》。新卡片在写入时会经过 lint 检查并被标记(绝不会被阻止),以便 Claude 可以修改它们。
工作原理(MCP Apps)
工具声明一个 ui:// 资源。当 Claude 调用该工具时,宿主(Claude Desktop)获取该资源,在沙箱化 iframe 中渲染其 HTML,将工具结果传递给界面,界面再通过 JSON-RPC 与宿主通信(用于给卡片评分并向模型报告进度)。
快速开始
前置要求
Node.js 20.11+
连接到 Claude Desktop
打开 Settings > Developer > Edit Config,在 mcpServers 下添加 Memora:
{
"mcpServers": {
"memora": {
"command": "npx",
"args": ["-y", "@servation/memora-mcp", "--stdio"]
}
}
}然后从系统托盘完全退出 Claude Desktop 并重新启动。memora 会出现在 Settings > Developer 下,并预装了几个示例牌组。
你的牌组存储在 ~/.memora/decks.json 中(可以用 MEMORA_DECKS 环境变量覆盖该路径)。可以手动编辑该文件,也可以让 Claude 来管理。
git clone https://github.com/Servation/memora-mcp.git
cd memora-mcp
npm install
npm run build使用绝对路径将配置指向构建后的入口(牌组随后存放在仓库的 data/decks.json 中):
{
"mcpServers": {
"memora": {
"command": "node",
"args": ["C:\\path\\to\\memora-mcp\\dist\\main.js", "--stdio"]
}
}
}试试看(在 Claude Desktop 聊天中)
review my World Capitals deckmake me a deck of 10 Spanish travel phrasesmake a reversible deck of 10 Spanish words(双向练习)make a fill-in-the-blank deck about the water cycle(完形填空卡片)quiz me with 10 multiple-choice questions on the solar systemturn what we just discussed into a deck called "Photosynthesis"study my LLM categorywhat's due today?
技术栈
服务端:TypeScript、
@modelcontextprotocol/sdk以及@modelcontextprotocol/ext-apps,stdio 传输(也可使用 Streamable HTTP)。界面:React 加 Vite,通过
vite-plugin-singlefile打包为单个内联 HTML 文件。调度:
ts-fsrs(FSRS)。构建后运行时只需纯
node(不需要 bun 或 tsx)。
牌组格式
{
"Deck Name": [
{ "front": "Capital of France?", "back": "Paris" }
]
}安装后存储在
~/.memora/decks.json中(从源码运行时为data/decks.json);可用MEMORA_DECKS覆盖。实时读取(mtime 缓存)。
create_deck、create_quiz和grade_card会以原子方式写入此处。测验卡片会添加
"options": ["...", "..."];其back是正确选项。完形填空卡片在正面将空白写成
[...],隐藏的词语作为back。随着你的复习,卡片会获得
due日期和 FSRSsrs块;没有这些的卡片会被视为新卡片。保持其为有效的 JSON,否则服务器会回退到内置的默认牌组。
项目结构
memora-mcp/
├── server.ts # MCP tools + the ui:// resource
├── decks.ts # data model, decks.json storage, result builder
├── scheduling.ts # FSRS scheduling + review ordering
├── main.ts # entry: stdio (Claude Desktop) or Streamable HTTP
├── mcp-app.html # UI entry HTML (bundled by Vite)
├── src/
│ ├── mcp-app.tsx # review orchestrator (flip / quiz / cloze, grade -> model)
│ ├── deck-lib.tsx # tree, mind map, card list, quiz/cloze views, helpers
│ ├── mcp-app.module.css
│ └── global.css # host theme variable fallbacks (light/dark)
├── data/decks.json # editable decks, read live
├── media/ # README images
├── vite.config.ts # single-file bundle config
└── tsconfig*.json开发
npm run dev # vite watch (UI) plus tsx server on http://localhost:3001/mcp
npm run typecheck # tsc --noEmit为了快速本地迭代,你还可以针对 ext-apps 仓库 中的 MCP Apps 参考宿主(basic-host)运行该应用。
路线图
待办事项见 TODO.md:npm + MCP Registry 发布、跨客户端托管(Streamable HTTP)、围绕解析和调度的测试,以及一个真实的屏幕录制演示 GIF。
许可证
Available Tools
10 toolscreate_deckCreate DeckA
Create (or extend) a flashcard deck from cards you generate based on the user's request or the current conversation, then display it for review. Use "::" in deck_name to nest under a category (e.g. "LLM::Attention"). The deck persists to data/decks.json.
Follow Memora's card-quality rules (based on Wozniak's '20 Rules of Formulating Knowledge'). The front is the prompt/question, the back is the answer:
Minimum information (atomic): each card tests exactly one fact or concept. Split complex material into several simple cards; never ask for lists or paragraph answers.
Concise answers: the back is ideally 1-5 words (a name, date, term, or single concept), never a sentence or paragraph.
Active recall: make the front a specific question (not 'Explain X'), or a cloze deletion: write the blank as "[...]" in the front and the hidden term as the back (e.g. front "The Transformer was introduced in [...].", back "2017").
Unambiguous: each front must point to exactly one correct answer.
Set reverse=true to also add the back->front version of each non-cloze card (useful for vocabulary or term/definition pairs that should be drilled both ways).
| Name | Required | Description | Default |
|---|---|---|---|
| cards | Yes | Flashcards generated from the user's request or the conversation. | |
| append | No | If true and the deck already exists, append to it; otherwise replace/create. | |
| reverse | No | If true, also add the reverse (back -> front) of each non-cloze card. | |
| deck_name | Yes | Name for the deck to create or add to ("::" nests it). |
Output Schema
| Name | Required | Description |
|---|---|---|
| deck | Yes | |
| cards | Yes | |
| count | Yes | |
| dueCount | Yes | |
| newCount | Yes | |
| quizDecks | No | |
| availableDecks | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully covers behavioral traits: persistence to data/decks.json, card-quality rules, and the effect of append (replace vs. append) and reverse. It also details the nesting behavior with '::'.
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 well-structured with front-loaded purpose and detailed rules. It is slightly verbose due to card-quality rules, but every sentence is justified for correct usage.
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?
Given the tool's complexity with 4 parameters and custom card-quality rules, the description is complete. It covers creation, extension, nesting, card formatting, and the effect of parameters. The presence of an output schema covers return values.
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 coverage is 100%, so baseline is 3. The description adds significant value by explaining deck_name nesting with '::', detailed card-quality rules (not in schema), and the reverse parameter. It does not add much to append parameter but overall enhances understanding.
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 it creates or extends a flashcard deck from cards generated based on user request or conversation. It distinguishes itself from siblings like create_quiz and study by focusing on deck creation and extending.
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?
The description provides explicit guidance on when to use the tool: 'from cards you generate based on the user's request or the current conversation.' It also explains the append and reverse parameters for extension. However, it does not explicitly mention when not to use it or alternatives like edit_card.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_quizCreate QuizA
Create (or extend) a multiple-choice quiz deck from questions you generate based on the user's request or the conversation, then display it for review. Use "::" in deck_name to nest under a category. Persists to data/decks.json and is reviewed like flashcards with spaced repetition.
Each question: a clear, specific prompt; 3 to 4 concise options with exactly ONE correct answer and plausible (not obviously wrong) distractors. The answer must match one of the options exactly.
| Name | Required | Description | Default |
|---|---|---|---|
| append | No | If true and the deck exists, append; otherwise replace/create. | |
| deck_name | Yes | Name for the quiz deck to create or add to ("::" nests it). | |
| questions | Yes | Multiple-choice questions you generate. |
Output Schema
| Name | Required | Description |
|---|---|---|
| deck | Yes | |
| cards | Yes | |
| count | Yes | |
| dueCount | Yes | |
| newCount | Yes | |
| quizDecks | No | |
| availableDecks | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. It discloses persistence to data/decks.json, display for review, and spaced repetition. However, it does not explain the behavior of the 'append' parameter (whether it replaces or extends) beyond implying both are possible.
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?
Two concise paragraphs; first sentence captures main purpose, second paragraph details question requirements. No unnecessary sentences, efficiently structured.
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?
Covers creation, display, persistence, and question requirements. Output schema exists so return values are covered. Missing explicit handling of 'append' behavior, but overall sufficient for an AI agent to use correctly.
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 coverage is 100%, baseline 3. Description adds value by explaining deck_name nesting ('::') and providing detailed formatting rules for questions (clear prompt, 3-4 options, one correct answer, plausible distractors), which goes beyond schema.
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?
Description clearly states the verb 'create (or extend)' and resource 'multiple-choice quiz deck', distinguishing it from sibling tool 'create_deck' by specifying it's for quiz decks with automated question generation based on user request.
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?
Description indicates when to use (user wants a quiz), how to structure deck names ('::' nesting), and question formatting rules. It does not explicitly exclude alternatives but provides sufficient context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_cardDelete CardA
Delete a single card from a deck, identified by its front text. Refuses to delete a deck's last card (delete the deck instead).
| Name | Required | Description | Default |
|---|---|---|---|
| front | Yes | The card's front text (identifies the card). | |
| deck_name | Yes | Deck the card belongs to. |
Output Schema
| Name | Required | Description |
|---|---|---|
| deck | Yes | |
| cards | Yes | |
| count | Yes | |
| dueCount | Yes | |
| newCount | Yes | |
| quizDecks | No | |
| availableDecks | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It discloses the refusal to delete the last card, which is a key behavioral trait. However, it does not mention other aspects like permissions or irreversibility, though 'delete' implies destructiveness.
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?
Two sentences, no unnecessary words. First sentence states core purpose, second adds critical constraint. Efficient and well-structured.
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 simple tool with full schema coverage and an existing output schema, the description is complete. It covers parameters, behavior, and usage limitations.
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 coverage is 100% and description adds no new parameter meaning beyond what the schema already provides. The mention of 'front text' is redundant with schema description.
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?
Description clearly states the verb 'delete' and resource 'card' with precise identification by front text. Unambiguous and distinguishes from sibling tools like delete_deck and edit_card.
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?
Explicitly says when not to use (last card) and provides alternative (delete_deck). This is direct usage guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_deckDelete DeckA
Delete a deck and all its cards. Refuses to delete the only remaining deck.
| Name | Required | Description | Default |
|---|---|---|---|
| deck_name | Yes | Deck to delete. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses that deletion affects both deck and cards, and that it refuses to delete the last deck. This adequately conveys destructive behavior and a key exception.
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 two sentences, direct, and front-loaded with the core action and a critical constraint. No unnecessary words.
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 simple tool with one parameter and no output schema, the description covers the essential functionality (delete deck and cards) and a key constraint (refusing to delete the only deck), making it sufficiently complete.
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?
There is only one parameter, 'deck_name,' with schema description 'Deck to delete.' The tool description does not add additional meaning beyond the schema. With 100% schema coverage, baseline score 3 is appropriate.
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 tool deletes a deck and all its cards, distinguishing it from sibling tools like 'delete_card' (single card) and 'rename_deck' (rename only).
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?
The description provides a clear constraint: 'Refuses to delete the only remaining deck,' which guides when not to use it. However, it does not explicitly state when to use this tool over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
due_todayDue TodayA
Summarize what is due to review right now across all decks: per-deck and total due/new counts. Pull-based (call it to see the summary); it does not appear on its own.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| date | Yes | |
| decks | Yes | |
| totalDue | Yes | |
| totalNew | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states the tool is pull-based and non-automatic, but does not disclose whether it is a read-only operation or any other behavioral traits.
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 two short, front-loaded sentences. Each sentence adds value: the first states the purpose, the second clarifies usage behavior. No waste.
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?
Given zero parameters and an output schema, the description fully covers what the tool does and how it behaves. It is complete for a summary tool.
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?
There are no parameters, so the baseline is 4. The description does not add parameter information, but none is needed.
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 'Summarize' and the resource 'what is due to review right now across all decks', specifying the output as per-deck and total due/new counts. This distinguishes it from sibling tools like review_deck or create_deck.
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?
The description notes that the tool is pull-based and does not appear on its own, providing clear context for when to call it. However, it does not explicitly compare it to alternatives like review_deck or study, though the distinction is implied by the summary nature.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
edit_cardEdit CardA
Edit a card's front and/or back in a deck, identified by its current front text, then re-render the deck. Keep edits within Memora's card-quality rules (atomic, concise 1-5 word answers, unambiguous).
| Name | Required | Description | Default |
|---|---|---|---|
| front | Yes | The card's CURRENT front text (identifies the card to edit). | |
| new_back | No | New back text. Omit to keep the current back. | |
| deck_name | Yes | Deck the card belongs to. | |
| new_front | No | New front text. Omit to keep the current front. |
Output Schema
| Name | Required | Description |
|---|---|---|
| deck | Yes | |
| cards | Yes | |
| count | Yes | |
| dueCount | Yes | |
| newCount | Yes | |
| quizDecks | No | |
| availableDecks | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It mentions re-rendering the deck and identification by current front text, but does not detail side effects, permissions, or error conditions.
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?
Two concise sentences; front-loaded with the action and resource, followed by essential quality constraints. No wasted words.
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?
Despite having an output schema, the description lacks information on error handling, mutability, or prerequisites. For a tool with 4 parameters and required fields, it provides minimum viable completeness.
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 coverage is 100%, so parameters are well-documented. Description adds value by clarifying that the 'front' parameter identifies the card and that edits apply to front and/or back, but does not substantially extend schema meaning.
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 that the tool edits a card's front and/or back, identified by its current front text, and distinguishes it from sibling tools like delete_card. It uses a specific verb-resource combination.
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?
The description provides guidelines on card-quality rules but does not explicitly specify when to use this tool vs alternatives (e.g., create_deck, delete_card) or mention exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
grade_cardGrade CardA
Record a spaced-repetition review result for a single card and update its FSRS schedule in data/decks.json. Called by the flip-card UI; not for direct model use.
| Name | Required | Description | Default |
|---|---|---|---|
| front | Yes | The card's front text (identifies the card). | |
| correct | Yes | Whether the user got the card right. | |
| deck_name | Yes | Deck the card belongs to. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses file update behavior but lacks details on idempotency, error handling, or what happens if the card doesn't exist.
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 two sentences, front-loaded, with no unnecessary words. Every sentence adds value.
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?
Covers purpose, usage boundary, and key behavior. Lacks mention of preconditions like card existence, but given UI usage and simplicity, it is mostly complete.
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 coverage is 100%, so baseline is 3. The description adds meaning by explaining that the result is a spaced-repetition review that updates the FSRS schedule, providing context beyond the schema descriptions.
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 action (record review result and update FSRS schedule), the resource (single card, data/decks.json), and distinguishes from sibling tools by specifying it's for a single card and called by the flip-card UI, not for direct model use.
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?
The description indicates it is called by the flip-card UI and not for direct model use, providing clear context. However, it does not explicitly list alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
rename_deckRename DeckA
Rename a deck, preserving its cards and schedules. Use "::" in the new name to move it under a category. Fails if a deck with the new name already exists.
| Name | Required | Description | Default |
|---|---|---|---|
| new_name | Yes | New deck name ("::" nests it under a category). | |
| deck_name | Yes | Current deck name. |
Output Schema
| Name | Required | Description |
|---|---|---|
| deck | Yes | |
| cards | Yes | |
| count | Yes | |
| dueCount | Yes | |
| newCount | Yes | |
| quizDecks | No | |
| availableDecks | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses preservation of cards/schedules and failure condition, but does not mention other aspects like authentication, rate limits, or idempotency.
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?
Three concise sentences: action+"preservation", formatting tip, failure condition. No fluff, front-loaded key information.
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 simple rename operation with a description and output schema, it is fairly complete. Could mention return value but not essential.
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 coverage is 100% with clear descriptions. The description adds useful context about using '::' for category nesting, which goes beyond the schema.
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 it renames a deck, preserving cards and schedules. This is specific and distinct from siblings like create_deck or delete_deck.
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?
The description provides clear context (rename operation) and mentions a failure condition (new name exists). However, it does not explicitly guide when to use this versus alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
review_deckReview DeckA
Return the flashcards of a single Memora deck and display them as an interactive flip-card review (due cards first). Available decks: "Geography::World Capitals", "Geography::Rivers", "Science::Solar System", "Language::Spanish Basics". Deck names use "::" to form a category tree; use the study tool to review a whole category. Decks are read live from data/decks.json.
| Name | Required | Description | Default |
|---|---|---|---|
| deck_name | No | Deck to review. Omit or pass an unknown name to get the first available deck. |
Output Schema
| Name | Required | Description |
|---|---|---|
| deck | Yes | |
| cards | Yes | |
| count | Yes | |
| dueCount | Yes | |
| newCount | Yes | |
| quizDecks | No | |
| availableDecks | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the data source ('read live from data/decks.json') and hints at read-only behavior by stating it 'returns' and 'displays' flashcards. No destructive actions are implied, adding needed transparency.
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 concise with 4 sentences, each adding necessary information: purpose, available decks, comparison to sibling, and data source. No redundant or vague language.
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?
Given the tool's simplicity (1 optional parameter, no nested objects, no annotations) and the existence of an output schema, the description covers all needed context: what it does, which decks exist, how to use the parameter, and where data comes from. No gaps.
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 coverage is 100%, so baseline is 3. The description adds extra value by listing available deck names (making selection easier) and explaining the fallback behavior when the deck name is omitted or invalid, which the schema does not cover.
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 tool's function: returning flashcards of a single deck and displaying them as an interactive review, prioritizing due cards. It lists specific available decks and distinguishes from the sibling 'study' tool by noting that 'study' reviews a whole category, while 'review_deck' is for a single deck.
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?
The description explicitly mentions an alternative tool ('study' for whole categories) and explains default behavior when the deck name is omitted or unknown. It does not explicitly state when not to use this tool, but the guidance is clear enough for an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
studyStudy CategoryA
Study every card under a category node of the deck tree. Deck names use "::" to nest (e.g. "LLM::Attention"); studying a node reviews all decks at or under that path, merged and shuffled into one session. Omit path to study all decks. Each card stays attributed to its source deck.
| Name | Required | Description | Default |
|---|---|---|---|
| path | No | Category path, e.g. "LLM" or "LLM::Attention". Omit to study all decks. |
Output Schema
| Name | Required | Description |
|---|---|---|
| deck | Yes | |
| cards | Yes | |
| count | Yes | |
| dueCount | Yes | |
| newCount | Yes | |
| quizDecks | No | |
| availableDecks | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. It discloses merging, shuffling, and attribution behavior. Could explicitly state non-destructive nature, but current detail is adequate.
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?
Four sentences, front-loaded main purpose, efficient. Minor redundancy (e.g., 'merged and shuffled' could be assumed from 'study'). Still well-structured.
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?
Given single optional parameter, output schema exists (reducing need for return value description), and context signals show low complexity. Description covers behavior sufficiently for effective use.
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 coverage is 100%, and description adds value by explaining path format ('::' nesting) and the effect of omission. Enhances schema meaning.
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 'study' and resource 'cards under a category node', explains nesting with '::', and distinguishes from siblings like 'review_deck' by focusing on category vs. single deck.
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?
Describes when to omit path (study all decks) and that studying a node covers all subdecks. Does not explicitly mention when not to use vs. specific sibling tools, but context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
10 tool updates
v0.1.1- First observed
create_deck - First observed
create_quiz - First observed
delete_card - First observed
delete_deck - First observed
due_today - First observed
edit_card - First observed
grade_card - First observed
rename_deck - First observed
review_deck - First observed
study
TDQS
Scored across 10 tools
Each tool targets a distinct action: deck/quiz creation, card/deck deletion, editing, renaming, reviewing single decks or categories, grading, and summary. No two tools have overlapping purposes; descriptions clearly differentiate them.
Most tools follow a verb_noun pattern (create_deck, delete_card, etc.), but 'due_today' is a noun phrase and 'study' is a bare verb, breaking the consistency. This mix could confuse an agent predicting tool names.
10 tools is well-scoped for a flashcard/quiz application. Each tool serves a necessary function in the creation, management, review, and scheduling lifecycle without being excessive or sparse.
The tool set covers CRUD operations, review, and scheduling. However, there is no tool to list all decks or view cards without triggering a review session, which is a minor gap that could hinder agent workflows.
Maintenance
Related MCP Connectors
Read, write, and conversationally review open-source flashcards through split read/write MCP tools.
- FlipnemOAuthcom.flipnem
Build and study spaced-repetition flashcards with your agent.
Spaced-repetition flashcards your AI writes, quizzes you on by voice, and schedules with FSRS.
- EngrAmoOAuthapp.engramo
Create and study EngrAmo spaced-repetition flashcards from your AI client.
Related MCP Servers
- AlicenseAqualityCmaintenanceAn MCP server that integrates Claude with Anki flashcards, allowing users to review due cards and create new flashcards directly through conversation.1413MIT
- AlicenseAqualityDmaintenanceIntegrates EduChain's educational content generation capabilities with Claude Desktop, enabling creation of multiple-choice questions, comprehensive lesson plans, and flashcards for any educational topic.31MIT
- AlicenseNot gradedqualityNot gradedmaintenanceConnects Claude to Anki flashcard software via AnkiConnect, enabling users to review due cards, create flashcards, and manage spaced repetition learning through natural language conversations.MIT
- AlicenseCqualityBmaintenanceFlashcard AI - MCP server providing AI-powered tools and automation by MEOK AI Labs46 npm90 PyPIMIT