What can you do with this server?

This server provides a headless spaced-repetition flashcard system via MCP, letting agents create, review, and manage cards with FSRS scheduling. * Author cards: add_card(front, back) creates a new flashcard and schedules it (due immediately). * List due cards: due_cards() returns cards due now, optionally filtered by deck or limited count, for quizzing. * Record recall: grade_card(card_id, rating) grades a review (again/hard/good/easy) and updates the FSRS schedule. * Edit card content: edit_card() changes front/back/deck without altering the existing schedule. * Suspend/unsuspend cards: Temporarily shelve or restore cards without losing history. * List all cards: list_cards() gives an overview regardless of due date, including reps and suspension status. * Delete cards: delete_card() permanently removes a card. * Get statistics: stats() shows total cards, due now, reviews, and deck breakdowns.

How do I use srs-mcp?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@srs-mcp show me my due cards" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

de en es ja ko ru zh

srs-mcp

by klutometis

Overview Schema Source Related Servers Discussions Admin

Python

Hybrid

srs-mcp

Agent-agnostic MCP server for spaced-repetition learning — no Anki GUI, no Xvfb, no AnkiConnect. Bring your own agent; this brings the card box + the scheduler.

It wraps FSRS (the Free Spaced Repetition Scheduler, the same algorithm modern Anki uses) around a tiny SQLite store, so an agent can author cards, see what's due, and record recall — entirely headless.

Why not headless Anki?

Driving the Anki desktop app headless means Qt + a virtual framebuffer (Xvfb) + the AnkiConnect add-on — brittle and version-coupled. The anki PyPI package can drive a real .anki2 collection GUI-less if you need interop with your phone's Anki. But if you just want spaced repetition behind an API, you don't need Anki at all: FSRS is a library, and this server is ~200 lines around it.

Related MCP server: flashcard-mcp

Tools

add_card(front, back) -> {card_id, due} — author + schedule a card. Keep back short — a word or a phrase; a card you can't grade in seconds is a note, not a flashcard
due_cards(q=None, limit=20) -> [{card_id, front, back, deck, due}] — what's due now, optionally narrowed to a topic (q="horace")
grade_card(card_id, rating) -> {card_id, rating, next_due, reps} — record recall (again/hard/good/easy, or 1-4)
edit_card(card_id, front=None, back=None) — edit content in place; schedule is preserved (fix typos / shorten a long answer instead of duplicating)
suspend_card(card_id) / unsuspend_card(card_id) — shelve a card (kept with its history, removed from the due queue) / restore it
list_cards(q=None, limit=50) — overview regardless of due date
delete_card(card_id) — remove one (reset / cleanup)
stats(deck=None) -> {total, due_now, suspended, reviews, decks}

Finding cards: search, not decks

Cards are found by searching their text — due_cards(q="horace") — rather than by filing them into decks up front. Nothing writes the deck field any more; put the topic in the card itself ("Horace, Odes 1.11: …") and it stays findable.

Decks were a single-valued, free-text, exact-match label with no per-deck scheduling attached, so they bought nothing a search doesn't, and cost accuracy: on the deck this was measured against, agents had invented ten names for Horace across five separator conventions, so the best possible deck="Horace" returned 20 of 97 Horace cards while q="horac" returns 89 — including ones misfiled under Talks. The column and the deck= filter on due_cards/list_cards/stats remain for cards labelled by older versions. See plans/002-decks.md.

The review loop: due_cards → quiz the user with front → check against back → grade_card. FSRS computes the next due date from the rating.

Run

uv sync
# HTTP (default; for Railway / remote agents)
PORT=8000 uv run srs-mcp
# or stdio (local agent)
MCP_TRANSPORT=stdio uv run srs-mcp

Storage

Two backends, chosen at startup:

Postgres (shared deck) — set SRS_DATABASE_URL (or DATABASE_URL) to a Postgres connection string (e.g. a Neon DB). Every deployment that points at the same URL reads/writes one shared deck, so you can add and review cards from anywhere (local, Railway, etc.). FSRS card ids are large, so the cards.card_id column is BIGINT on Postgres. Requires the psycopg dependency (already declared).
SQLite (fallback) — when no *DATABASE_URL is set, cards live in a SQLite file at SRS_DB (default ./srs.db). Single-host / offline. In a SQLite-on-Railway setup, mount a volume at /data and keep SRS_DB=/data/srs.db so the box survives redeploys.

The schema is identical (table cards) and auto-created on first use.

Available Tools

9 tools

add_cardA

Author a new flashcard and schedule it. front is the prompt/question, back is the answer. Optional deck groups cards (default 'default'). Returns JSON {card_id, due}. The card is due immediately (first review).

ParametersJSON Schema

Name	Required	Default
`back`	Yes
`deck`	No	default
`front`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.6/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses that the card is due immediately and returns JSON with card_id and due. Covers scheduling and first review. No annotations provided, but description adequately conveys behavioral traits for a creation tool.

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, front-loaded with purpose, no wasted words. Efficiently covers all essential information.

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?

Complete for a simple creation tool. Covers purpose, parameters, return value, and scheduling. Output schema is present, so return details are handled. No gaps given the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage, but the description explains front as prompt/question, back as answer, and deck as group with default. Adds significant meaning beyond schema types.

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?

Clearly states the verb 'Author' and resource 'flashcard', and mentions scheduling. Distinguishes from sibling tools like delete_card, edit_card, grade_card, etc. by focusing on creation.

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?

Provides clear context for when to use (creating a new card) and explains optional 'deck' parameter with default. Lacks explicit when-not or alternatives, but the purpose is distinct from siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

delete_cardC

Delete a card by id (reset / cleanup).

ParametersJSON Schema

Name	Required	Description	Default
`card_id`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavior. It says 'delete' but adds '(reset / cleanup)' which suggests non-permanent deletion, but this is not elaborated. No mention of consequences, reversibility, or permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Very short, but conciseness is not a virtue when it sacrifices clarity. The structure is front-loaded but lacks sufficient detail for safe agent use.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Although operations with 1 parameter and an output schema could be simple, the description fails to explain return values, side effects, or the precise meaning of '(reset / cleanup)'. This is incomplete for a deletion tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description only says 'by id'. It adds no detail about the card_id parameter beyond what the schema already provides (integer, required). Ambiguity remains about acceptable values.

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), resource (card), and scope (by id). It also distinguishes from sibling tools like edit_card or suspend_card, which have different actions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use delete vs. alternatives like suspend_card. The parenthetical '(reset / cleanup)' hints at a specific use case but is ambiguous and not explicitly explained.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

due_cardsA

List cards due for review now (due <= now), soonest first. Optionally filter by deck. Returns a JSON array of {card_id, front, back, deck, due}. Quiz the user with front, check against back, then call grade_card. Returns '[]' when nothing is due.

ParametersJSON Schema

Name	Required	Description	Default
`deck`	No
`limit`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4/5.0

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 return format, sorting, empty case, and optional filter. However, it omits behavior related to the limit parameter and does not explicitly state that it is read-only or safe.

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 extremely concise: three sentences that front-load the main purpose, then cover options, return format, and usage hint. 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?

Given the simple schema (two parameters) and the presence of an output schema, the description covers the essential aspects: purpose, filter, return format, and usage. The omission of the limit parameter's meaning is a minor gap that slightly reduces 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?

The description clarifies the `deck` parameter as a filter, adding meaning beyond the schema. However, the `limit` parameter (default 20) is not mentioned at all, leaving its purpose unclear. With 0% schema coverage, the description only partially compensates.

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 lists cards due for review, with a specific scope (due <= now) and ordering (soonest first). It distinguishes from siblings like list_cards by focusing on due cards, and it explicitly outlines the return format and workflow.

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 implies a workflow: fetch due cards, then grade each using grade_card. It mentions filtering by deck. However, it does not explicitly compare with sibling tools like list_cards or state when not to use it, which would strengthen guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

edit_cardA

Edit a card's content without disturbing its schedule. Update any of front, back, deck (omit or pass null to leave unchanged); the FSRS review state (difficulty, stability, due date, reps) is preserved. Use this to fix typos or add context instead of creating a duplicate card. Returns JSON {card_id, front, back, deck}.

ParametersJSON Schema

Name	Required	Description	Default
`back`	No
`deck`	No
`front`	No
`card_id`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.6/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that FSRS review state (difficulty, stability, due date, reps) is preserved. It also specifies the return format (JSON with card_id, front, back, deck).

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 sentences, front-loaded with the core action and constraint. Every sentence adds value: purpose, parameters, usage advice, return format. 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?

Given 4 parameters, no annotations, and a mentioned output schema, the description covers all necessary info: what it does, how parameters work, behavioral traits, return format. It is complete for a simple update tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description adds full meaning: 'Update any of front, back, deck (omit or pass null to leave unchanged)'. It explains that card_id is required and optional parameters are nullable with default null.

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 'Edit', the resource 'card', and the key constraint 'without disturbing its schedule'. It distinguishes from sibling tools like add_card and delete_card.

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 says 'Use this to fix typos or add context instead of creating a duplicate card', providing clear usage guidance. It implies when to use (fix typos, add context) and when not (schedule changes).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

grade_cardA

Record a review of a card. rating is how well it was recalled: 'again' (forgot), 'hard', 'good', or 'easy' (1-4 also accepted). FSRS updates the schedule; returns JSON {card_id, rating, next_due, reps}.

ParametersJSON Schema

Name	Required	Description	Default
`rating`	Yes
`card_id`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.4/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so the description carries full burden. It discloses that FSRS updates the schedule and returns the expected JSON structure, but doesn't mention side effects like changing due dates or whether re-grading is allowed.

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 with no wasted words. First sentence states the action, second provides parameter details, schedule effect, and return format. Well-structured and front-loaded.

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 low-complexity tool with 2 required parameters and a simple return structure, the description covers all essential aspects: action, parameter values, effect (FSRS schedule update), and output format. No gaps given the sibling context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage, but the description fully explains rating values ('again', 'hard', 'good', 'easy' with 1-4 accepted) and implicitly defines card_id as identifying the card to grade. Adds significant meaning 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 'Record a review of a card' which is a specific verb+resource. It distinguishes from sibling tools (add, delete, edit, etc.) by focusing on the review/grading action.

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?

No explicit guidance on when to use or not use this tool versus alternatives. The purpose implies usage after a card is reviewed, but lacks prerequisites or context for appropriate invocation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_cardsA

List cards (newest first) regardless of due date, for an overview. Optionally filter by deck. Returns JSON array of {card_id, front, back, deck, due, reps, suspended}.

ParametersJSON Schema

Name	Required	Description	Default
`deck`	No
`limit`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.1/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full weight. Clearly indicates read-only behavior (list), sorting, optional filter, and return format. Lacks mention of authentication or rate limits, but sufficient for a simple list operation.

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, front-loaded with main purpose. 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?

Covers purpose, ordering, filter, and return structure. Output schema exists but description still details the returned fields. Adequate for a simple list tool.

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 0%, so description must compensate. Mentions `deck` as optional filter with some context, but does not explain accepted values or behavior when omitted. `limit` not explained. Adds partial meaning 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?

Clearly states verb (List), resource (cards), ordering (newest first), and scope (regardless of due date). Distinguishes from due_cards sibling by explicitly noting the lack of due date filtering.

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?

Implies usage via contrast with due_cards (lists all cards, not just due). Does not explicitly state when to use vs. other siblings or provide exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

statsA

Summary of the card box: total cards, how many are due now, total reviews, and the deck list. Optionally scope counts to one deck.

ParametersJSON Schema

Name	Required	Description	Default
`deck`	No

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description adequately conveys a read-only, non-destructive operation. It clearly indicates what the tool returns. However, it does not mention rate limits, required permissions, or potential empty results, which would be helpful.

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 one clear, well-structured sentence with no extraneous words. Every part contributes to understanding the tool's function.

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 the presence of an output schema (assumed to detail return values), the description covers the main outputs and parameter. Slight omission: it does not mention whether the deck list includes non-empty decks only or all decks.

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?

The description explains the sole optional parameter 'deck' as a filter to scope counts, adding meaning beyond the bare schema (which lacks descriptions). For a single parameter, this is sufficient.

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 provides a summary of the card box with specific components (total cards, due now, total reviews, deck list) and mentions optional scoping by deck. This distinguishes it from sibling tools like due_cards or list_cards.

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 implies the tool is for obtaining an overview, but it does not explicitly state when to use it versus siblings (e.g., 'for a quick overview, use stats; for detailed card info, use list_cards'). No when-not-to-use guidance is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

suspend_cardA

Shelve a card: keep it (with its full history and schedule) but remove it from the due queue, so it won't surface in due_cards until unsuspended. Reversible, non-destructive alternative to delete_card for cards you're unsure about. Returns JSON {card_id, suspended}.

ParametersJSON Schema

Name	Required	Description	Default
`card_id`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A4.5/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses reversibility, non-destructiveness, retention of history and schedule, and return format. No annotations exist, so description compensates well, though minor details like behavior on already-suspended cards omitted.

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, front-loaded with action and key details. No wasted 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?

Given simplicity (1 param, no annotations), description covers purpose, usage, behavior, return format fully. Output schema exists but description already provides key return info.

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?

Only one parameter (card_id), self-explanatory from context. Schema coverage is 0%, but the parameter is trivial and description doesn't add extra semantics beyond obvious.

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?

Clearly defines the tool as shelving a card, keeping history and schedule but removing from due queue. Distinguishes from siblings like delete_card and unsuspend_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 states it is a reversible, non-destructive alternative to delete_card for uncertain cards, providing clear when-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

unsuspend_cardA

Un-shelve a previously suspended card, returning it to the review queue (it becomes due again per its existing schedule). Returns JSON {card_id, suspended}.

ParametersJSON Schema

Name	Required	Description	Default
`card_id`	Yes

Output Schema

ParametersJSON Schema

Name	Required	Description
`result`	Yes

TDQS

A3.9/5.0

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 the return format and that the card becomes due per its existing schedule, but does not mention prerequisites (e.g., card must be suspended) or side effects like schedule changes.

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 impactful sentences with no wasted words. It front-loads the action and includes the return format compactly.

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 tool with one parameter and an output schema (mentioned in description), the description adequately covers purpose and basic behavior. It could mention that the card must be suspended, but overall it is sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter 'card_id' is not explained beyond the schema, and schema coverage is 0%. The description does not add meaning about what card_id is or how to obtain it, leaving ambiguity.

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: unsuspending a previously suspended card and returning it to the review queue. It uses a specific verb 'unsuspend' and resource 'card', and distinguishes from the sibling 'suspend_card'.

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 implies the tool should be used only on cards that are currently suspended, but does not explicitly state when not to use it or provide alternatives. The context 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.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

9 tool updatesv0.2.1Jul 14, 2026
- First observedadd_card
- First observeddelete_card
- First observeddue_cards
- First observededit_card
- First observedgrade_card
- First observedlist_cards
- First observedstats
- First observedsuspend_card
- First observedunsuspend_card

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4/5.0

Scored 2026-07-14 22:10 across 9 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: adding, deleting, editing, listing, reviewing, grading, stats, suspending, and unsuspending cards. No two tools overlap in functionality.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern in snake_case, e.g., add_card, delete_card, grade_card. Names are predictable and readable.

Tool Count5/5

9 tools is well-scoped for a spaced repetition system, covering all essential operations without bloat. Each tool earns its place.

Completeness4/5

Covers core CRUD, review workflow, statistics, and suspension. Missing explicit deck management (e.g., create/delete deck) but decks are manageable via card properties.

Maintenance

ActivityMaintained

ResponsivenessUnresponsive

Resources

Need Help?

Related Servers

Related MCP Connectors

FlipnemOAuth
com.flipnem
Build and study spaced-repetition flashcards with your agent.
Education & Learning Tools Knowledge & Memory Note Taking
2
Flash AOAuth
com.flashmemorize
Spaced-repetition flashcards your AI writes, quizzes you on by voice, and schedules with FSRS.
Education & Learning Tools Speech Processing
1711
agentbay-mcp AOAuth
io.github.thomasjumper
Persistent memory and knowledge management for AI agents with semantic search and 50+ tools.
Knowledge & Memory Autonomous Agents Agent Orchestration
21
Quizlar — voice-powered AI flashcards with spaced repetitionOAuth
io.github.quizlar
Voice-led, FSRS-scheduled flashcards from YouTube, PDFs, web, or text. Auto-graded quizzes.
Education & Learning Tools Speech Processing Knowledge & Memory
2

Related MCP Servers

anki-mcp
Education & Learning Tools Knowledge & Memory
mybuddymichael
A
license
Not graded
quality
D
maintenance
Enables LLMs to interact with Anki flashcard collections, including deck management, note search, viewing contents, and editing fields.
Updated a year ago (2025-07-31 02:52 UTC)
9 npm
MIT
flashcard-mcp
Education & Learning Tools Knowledge & Memory
cokovali10-sketch
A
license
Not graded
quality
C
maintenance
A lightweight MCP server that adds spaced-repetition flashcards (SM-2) to AI assistants, storing data locally in SQLite and enabling card creation, review, and scheduling.
Updated a month ago (2026-08-11 09:35 UTC)
MIT
Open Review Assistant
Education & Learning Tools Knowledge & Memory
roychenccecc
A
license
Not graded
quality
C
maintenance
Provides a privacy-first adaptive review engine with local SQLite storage, enabling item creation, due review retrieval, grading, and statistics via MCP tools.
Updated a month ago (2026-08-16 16:37 UTC)
MIT
Memory MCP Server
Knowledge & Memory Project Management
bsahane
A
license
Not graded
quality
B
maintenance
Enables AI agents to store, search, and manage persistent memories, todos, kanban boards, reminders, and progress trackers in a local SQLite database.
Updated a month ago (2026-08-23 00:05 UTC)
Apache 2.0