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Memora MCP

License: MIT MCP Apps TypeScript React

Verwandle jedes Gespräch in eine interaktive Lernsitzung, direkt in Claude Desktop. Frag Claude, ein Deck zu erstellen – es generiert die Karten und rendert sie als Inline-Übersicht, die du durchklicken kannst: Drehe Karteikarten um, beantworte Multiple-Choice-Quizze und fülle Lückentext-Lücken aus. Jede Antwort aktualisiert einen Spaced-Repetition-Zeitplan, und die Ergebnisse fließen an Claude zurück, damit es genau das weiter üben kann, was du noch nicht konntest.

Keywords: Model Context Protocol, MCP-Server, MCP-Apps, Claude Desktop, Karteikarten, Quiz, Spaced Repetition, SRS, FSRS, Anki-Alternative.

Basierend auf der MCP-Apps-Erweiterung (SEP-1865): MCP-Kernspezifikation 2025-11-25 plus Apps-Erweiterung 2026-01-26.

Drei Lernarten, inline in Claude dargestellt

Funktionen

Drei Lernarten, alle inline dargestellt und alle nach dem gleichen Schema bewertet:

  • Karteikarten: Zum Umdrehen klicken, dann mit Gewusst / Nicht gewusst bewerten.

  • Multiple-Choice-Quiz: Eine Option auswählen und die richtige/falsche Antwort erscheint sofort.

  • Lückentext: Die Lücke wird an Ort und Stelle aufgedeckt, sodass der Satz intakt bleibt. Schreib eine Lücke als [...] auf die Kartenvorderseite, und sie wird automatisch zu einer Lückentext-Karte.

Spaced Repetition: Jede Bewertung aktualisiert einen FSRS-Zeitplan pro Karte (über ts-fsrs). Schwache Karten tauchen also früher wieder auf, fällige Karten kommen zuerst. Frag „Was ist heute fällig?“ für eine Zusammenfassung über alle deine Decks.

Mit Kategorien organisieren: Nenne Decks mit :: geschachtelt (z. B. LLM::Attention). Durchsuche den Kategorienbaum oder denselben Baum als interaktive Mind-Map und lerne einen gesamten Zweig in einer zusammengeführten Sitzung. Quiz-Decks werden mit einem Badge markiert.

Decks verwalten: Decks und Karten direkt im Chat erstellen, erweitern, bearbeiten, umbenennen und löschen. Übergib beim Erstellen eines Decks reverse, um jede Karte auch in der umgekehrten Richtung zu üben (praktisch für Vokabeln).

Einfach JSON: Decks liegen in data/decks.json, das bei jedem Aufruf live gelesen wird. Du kannst sie manuell bearbeiten oder von Claude anlegen lassen. Keine Datenbank, kein externer Dienst.

Decks als Kategorienbaum oder Mind-Map durchsuchen

Related MCP server: EduChain MCP Server

Die Tools

Nur review_deck und study öffnen das Inline-Karteikarten-UI; alle anderen Tools liefern eine textuelle Zusammenfassung. So stört das Bearbeiten oder Erstellen im Chat nicht durch unerwartet aufgehende Widgets.

Tool

Was es tut

review_deck

Öffnet ein Deck zur Wiederholung (fällige Karten zuerst, pro Sitzung begrenzt).

study

Wiederholt einen ganzen Kategorie-Unterbaum, zusammengeführt in eine Sitzung (pro Sitzung begrenzt).

create_deck

Erzeugt Karteikarten oder Lückentext-Karten; reverse fügt außerdem Karten in umgekehrter Richtung hinzu.

create_quiz

Erzeugt Multiple-Choice-Fragen.

grade_card

Speichert ein Bewertungsergebnis und aktualisiert den FSRS-Zeitplan der Karte (von der UI aufgerufen).

due_today

Fasst zusammen, was über alle Decks fällig ist, und markiert Karten mit Lernschwierigkeiten (3+ Fehlversuche).

edit_card

Ändert Vorder- und/oder Rückseite einer Karte.

refine_card

Schlägt vor, eine Karte in atomare Einzelkarten zu zerlegen oder sie umzuschreiben, um das Verständnis zu testen.

apply_refinement

Speichert eine Überarbeitung, nachdem der Benutzer die vorgeschlagenen Karten genehmigt hat.

capture

Verwandelt etwas, das dir gerade Schwierigkeiten gemacht hat (einen Bug, eine falsch beantwortete Frage) in Kartenentwürfe.

apply_capture

Speichert erfasste Karten, nachdem der Benutzer sie genehmigt hat.

rename_deck

Benennt ein Deck um und verschiebt es auch im Kategorienbaum.

delete_card

Entfernt einen einzelnen Karte. (sollte "eine einzelne Karte" sein)

delete_deck

Entfernt ein ganzes Deck.

Die Kartengenerierung folgt den Qualitätsregeln von Memora (atomare Ein-Internation Karten, Antworten mit 1–5 Wörtern, aktives Abrufen, Eindeutigkeit, keine Hinweise auf die Lösung, praktische Anwendung vor Definition), die auf Wozniaks 20 Regeln zur Formulierung von Wissen basiert. Neue Karten werden beim Schreiben geltet und markiert (jedoch nie blockiert), damit Claude sie ablehnen kann.

Wie es funktioniert (MCP-Apps)

Ein Tool deklariert eine ui://-Ressource. Wenn Claude das Tool aufruft, holt der Host (Claude Desktop) diese Ressource, rendert das HTML in einem Sandbox-Service-iFrame, übergibt das Tool-Ergebnis an die UI, und die UI spricht über JSON-RPC mit dem Host (zur Bewertung der Karten und zum Melden des Fortschritts an das Modell).

Der MCP-Apps-Requestverlauf

Schnellstart

Voraussetzungen

  • Node.js 20.11+

Mit Claude Desktop verbinden

Öffne Einstellungen > Entwickler > Konfiguration bearbeiten und füge Memora unter mcpServers hinzu:

{
  "mcpServers": {
    "memora": {
      "command": "npx",
      "args": ["-y", "@servation/memora-mcp", "--stdio"]
    }
  }
}

Beende Claude Desktop dann vollständig (über das System-Tray) und starte es neu. memora erscheint unter Einstellungen > Entwickler, mit einigen Beispield-ecks vorinstalliert.

Deine Decks werden in ~/.memora/decks.json gespeichert (du kannst den Pfad über die Umgebungsvariable MEMORA_DECKS überschreiben). Bearbeite die Datei manuell oder lass Claude die Verwaltung übernehmen.

git clone https://github.com/Servation/memora-mcp.git
cd memora-mcp
npm install
npm run build

Richte die Konfiguration auf den gebauten Einstiegspunkt mit einem absoluten Pfad aus (die Decks liegen dann in data/decks.json des Repos):

{
  "mcpServers": {
    "memora": {
      "command": "node",
      "args": ["C:\\path\\to\\memora-mcp\\dist\\main.js", "--stdio"]
    }
  }
}

Ausprobieren (im Claude-Desktop-Chat)

  • review my World Capitals deck

  • make me a deck of 10 Spanish travel phrases

  • make a reusable deck of 10 Spanish words (übt beide Richtungen)

  • make a multiple-choice quiz on the solar system (übt falschliche)

  • turn what we just discussed into a deck called "Photosynthesis"

  • study my LLM category

  • what's due today?

Tech-Stack

  • Server: TypeScript, @modelcontextprotocol/sdk plus @modelcontextprotocol/ext-apps, stdio-Transport (Streamable HTTP ebenfalls verfügbar).

  • UI: React plus Vite, über vite-plugin-singlefile zu einer einzigen, eingebetteten HTML-Datei gebündelt.

  • Zeitplanung: ts-fsrs (FSRS).

  • Nach dem Build läuft das Ganze mit reinem node – ohne bun oder tsx.

Deck-Format

{
  "Deck Name": [
    { "front": "Capital of France?", "back": "Paris" }
  ]
}
  • Bei installierter Version gespeichert in ~/.memora/decks.json (aus dem Quellcode: data/decks.json); überschreibbar mit MEMORA_DECKS.

  • Liegt live beim Aufruf (mtime-gecacht). create_deck, create_quiz und grade_card schreiben atomar in die Datei.

  • Eine Quiz-Karte erhält ein Feld "options": ["...", "..."]; ihre back ist die richtige Antwort.

  • Eine Lückentext-Karte notiert die Lücke als [...] in der Vorderseite und den verborgenen Begriff als back.

  • Beim Wiederholen erhalten Karten ein fällig/-Datum und einen FSRS-srs`-Block; Karten ohne diese werden als neu behandelt.

  • Die Datei muss gültiges JSON bleiben, sonst fällt der Server auf ein eingebautes Standard-Deck zurück.

Projektstruktur

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

Entwicklung

npm run dev        # vite watch (UI) plus tsx server on http://localhost:3001/mcp
npm run typecheck  # tsc --noEmit

Für schnelle lokale Iteration kannst du die App auch gegen den MCP-Apps-Referenzhost (basic-host) aus dem ext-apps-Repository ausprobieren.

Roadmap

Siehe TODO.md für den Backlog: npm- und MCP-Registry-Veröffentlichung, clientübergreifend bit hosting (Streamable HTTP), Tests für Parsing und Planung sowie eine echte Screen-Capture-Demo als GIF.

Lizenz

MIT

Available Tools

10 tools
create_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:

  1. 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.

  2. Concise answers: the back is ideally 1-5 words (a name, date, term, or single concept), never a sentence or paragraph.

  3. 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").

  4. 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).

ParametersJSON Schema
NameRequiredDescriptionDefault
cardsYesFlashcards generated from the user's request or the conversation.
appendNoIf true and the deck already exists, append to it; otherwise replace/create.
reverseNoIf true, also add the reverse (back -> front) of each non-cloze card.
deck_nameYesName for the deck to create or add to ("::" nests it).

Output Schema

ParametersJSON Schema
NameRequiredDescription
deckYes
cardsYes
countYes
dueCountYes
newCountYes
quizDecksNo
availableDecksYes

TDQS

A4.6/5.0
Behavior5/5

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.

Conciseness4/5

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.

Completeness5/5

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.

Parameters4/5

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.

Purpose5/5

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.

Usage Guidelines4/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
appendNoIf true and the deck exists, append; otherwise replace/create.
deck_nameYesName for the quiz deck to create or add to ("::" nests it).
questionsYesMultiple-choice questions you generate.

Output Schema

ParametersJSON Schema
NameRequiredDescription
deckYes
cardsYes
countYes
dueCountYes
newCountYes
quizDecksNo
availableDecksYes

TDQS

A4.2/5.0
Behavior3/5

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.

Conciseness5/5

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.

Completeness4/5

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.

Parameters4/5

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.

Purpose5/5

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.

Usage Guidelines4/5

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).

ParametersJSON Schema
NameRequiredDescriptionDefault
frontYesThe card's front text (identifies the card).
deck_nameYesDeck the card belongs to.

Output Schema

ParametersJSON Schema
NameRequiredDescription
deckYes
cardsYes
countYes
dueCountYes
newCountYes
quizDecksNo
availableDecksYes

TDQS

A4.3/5.0
Behavior3/5

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.

Conciseness5/5

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.

Completeness5/5

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.

Parameters3/5

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.

Purpose5/5

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.

Usage Guidelines5/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
deck_nameYesDeck to delete.

TDQS

A4.3/5.0
Behavior4/5

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.

Conciseness5/5

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.

Completeness5/5

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.

Parameters3/5

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.

Purpose5/5

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.

Usage Guidelines4/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

Output Schema

ParametersJSON Schema
NameRequiredDescription
dateYes
decksYes
totalDueYes
totalNewYes

TDQS

A4.3/5.0
Behavior3/5

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.

Conciseness5/5

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.

Completeness5/5

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.

Parameters4/5

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.

Purpose5/5

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.

Usage Guidelines4/5

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).

ParametersJSON Schema
NameRequiredDescriptionDefault
frontYesThe card's CURRENT front text (identifies the card to edit).
new_backNoNew back text. Omit to keep the current back.
deck_nameYesDeck the card belongs to.
new_frontNoNew front text. Omit to keep the current front.

Output Schema

ParametersJSON Schema
NameRequiredDescription
deckYes
cardsYes
countYes
dueCountYes
newCountYes
quizDecksNo
availableDecksYes

TDQS

A3.7/5.0
Behavior3/5

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.

Conciseness5/5

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.

Completeness3/5

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.

Parameters3/5

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.

Purpose5/5

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.

Usage Guidelines3/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
frontYesThe card's front text (identifies the card).
correctYesWhether the user got the card right.
deck_nameYesDeck the card belongs to.

TDQS

A4.2/5.0
Behavior3/5

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.

Conciseness5/5

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.

Completeness4/5

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.

Parameters4/5

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.

Purpose5/5

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.

Usage Guidelines4/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
new_nameYesNew deck name ("::" nests it under a category).
deck_nameYesCurrent deck name.

Output Schema

ParametersJSON Schema
NameRequiredDescription
deckYes
cardsYes
countYes
dueCountYes
newCountYes
quizDecksNo
availableDecksYes

TDQS

A4.2/5.0
Behavior3/5

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.

Conciseness5/5

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.

Completeness4/5

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.

Parameters4/5

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.

Purpose5/5

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.

Usage Guidelines4/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
deck_nameNoDeck to review. Omit or pass an unknown name to get the first available deck.

Output Schema

ParametersJSON Schema
NameRequiredDescription
deckYes
cardsYes
countYes
dueCountYes
newCountYes
quizDecksNo
availableDecksYes

TDQS

A4.5/5.0
Behavior4/5

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.

Conciseness5/5

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.

Completeness5/5

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.

Parameters4/5

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.

Purpose5/5

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.

Usage Guidelines4/5

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.

ParametersJSON Schema
NameRequiredDescriptionDefault
pathNoCategory path, e.g. "LLM" or "LLM::Attention". Omit to study all decks.

Output Schema

ParametersJSON Schema
NameRequiredDescription
deckYes
cardsYes
countYes
dueCountYes
newCountYes
quizDecksNo
availableDecksYes

TDQS

A4.3/5.0
Behavior4/5

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.

Conciseness4/5

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.

Completeness4/5

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.

Parameters4/5

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.

Purpose5/5

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.

Usage Guidelines4/5

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.

  1. 10 tool updatesv0.1.1
    • First observedcreate_deck
    • First observedcreate_quiz
    • First observeddelete_card
    • First observeddelete_deck
    • First observeddue_today
    • First observededit_card
    • First observedgrade_card
    • First observedrename_deck
    • First observedreview_deck
    • First observedstudy

TDQS

A4.2/5.0

Scored across 10 tools

Disambiguation5/5

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.

Naming Consistency3/5

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.

Tool Count5/5

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.

Completeness4/5

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

ActivitySlowing
ResponsivenessNo issues

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