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MindDory Brain MCP Server

answering

MindDory Brain is answering right now. Last checked 12 min ago. It exposes 13 tools. Last commit 11 Sep 2026.

Free: turn your AI chats into spaced-repetition vocabulary. 13 tools, reads and writes.

Uptime history 48 days of history
48 days agonow
100.0%
Uptime 24h
91 of 91 checks
13
Tools
read from the server
428 ms
Response time
average over 24h
0
Stars
last commit 11 Sep 2026

What changed 10

Every tool that appeared, vanished or quietly changed what it asks for. Recorded since 20 August 2026. No other catalogue keeps this.

20 Aug 7 tools changed the parameters they ask for get_active_vocab, get_card, get_known_words and 4 more
20 Aug 2 tool descriptions were rewritten mark_demonstrated, mark_struggled
20 Aug a tool appeared check_words

Nothing serious here today

Today is the operative word: we check MindDory Brain every 15 minutes and re-read its code on every release. Watch it and you find out the day that stops being true.

Three servers free · no card

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 12 min ago.

run in your terminal
claude mcp add brain --transport http https://api.minddory.com/v1/brain/mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "brain": {
      "url": "https://api.minddory.com/v1/brain/mcp"
    }
  }
}
~/.codex/config.toml
[mcp_servers.brain]
url = "https://api.minddory.com/v1/brain/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "brain": {
      "url": "https://api.minddory.com/v1/brain/mcp"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "brain": {
      "url": "https://api.minddory.com/v1/brain/mcp"
    }
  }
}

Available tools 13

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

capture
capture_grammar_mistake
Log a grammar mistake the user just made in the target language, creating a grammar point in their Minddory deck. Use it proactively whenever the user writes a target-language sentence with a clear, correctable error (wrong tense, agreement, word_choice, word_order, missing or wrong article, preposition, gender, conjugation, spelling, pluralization). By connecting Minddory the user opted IN to automatic capture, so log it as you go - do not ask permission first or turn it into a yes/no question. The user connected Minddory to catch and review these patterns; you do not need to announce each log. Pass the original text + correction + error_type. Multiple mistakes in one message = multiple calls. VARIANT RULE: Always pass the user's full BCP-47 variant in the lang field (e.g. en-gb, not en) - get it from get_system_instructions on first turn. Before logging, check that the "error" is not actually a valid regional variant form (US past-simple vs UK present-perfect with "just/already", US "in the hospital" vs UK "in hospital", US "color" vs UK "colour", BR gerund vs PT "a + infinitive", etc.). When the variant is unspecified (base ISO only), treat ALL regional forms as valid. Better to skip a borderline call than to mark a valid variant form as wrong. error_type must be one of: tense, agreement, word_choice, word_order, article, preposition, spelling, pluralization, conjugation, gender, other. Feeds the user's Grammar Patterns view at app.minddory.com/grammar.
capture_word
Capture a target-language word or phrase to the user's Minddory vocabulary deck (a flashcard in the "Chat Discoveries" folder when the word is new, otherwise a context encounter). The user connected Minddory so their assistant builds their deck from real conversations, so use this proactively to log notable target-language vocabulary they encounter, use, or ask about. By connecting Minddory the user opted IN to automatic capture, so just capture as you chat - do not pause to ask permission for each word, and do not turn capturing into a yes/no question. You do not need to announce each capture, but answer honestly if the user asks what you have saved. Use the `words` array to capture several from one message; include a `gloss` (short source-language translation) and `context` (the sentence) when you can. Skip stop words, proper nouns, numbers, and words shorter than 3 characters (CJK / Hangul exempt). ALWAYS pass `lang` — the ISO code of the captured word's own language (you know it from the conversation); the call is rejected without it and the target language is never guessed. `source_lang` (the user's native language) is optional and defaults to their deck. This is the primary tracking signal of Minddory, so capture diligently.
mark
mark_demonstrated
Confidence-weighted spaced-repetition boost when the user has used a word correctly: the card moves further out in the review schedule. Logs an answer row even if no flashcard exists.
mark_struggled
Spaced-repetition degrade for a word the user just got wrong: the card comes back sooner. ease_factor drops, interval resets, repetitions reset.
active
get_active_vocab
Get the user's most actively encountered target-language words (from past capture_word + log_interaction events), ranked by frequency over a lookback window. Use to surface "frontier" words the user keeps touching when they ask "what should I learn next" or when you want context-aware suggestions.
card
get_card
Single card detail by word (case-insensitive). Returns translation, mastery, and last 10 events.
known
get_known_words
Words the user has verified known via flashcard practice. Paginated keyset on flashcards.id.
log
log_interaction
Append a generic interaction event to the answers log. Use for lookups, AI discussions, and reading-in-context signals.
queue
get_queue
Cards due now and due within the next 24 hours.
recent
get_recent_activity
Event log slice with optional surface filter and keyset pagination on answers.id.
system
get_system_instructions
Call this at the START of every new conversation, before your first reply, to load the user's Minddory setup and your role as their proactive language partner: CEFR level, target/source languages, due-card count, weak words, and how to capture. The user connected Minddory to actively improve their language through this chat, so use it to tailor your help to their level and goals. Pass `lang` when you know which language the user wants to practice right now - the language they are conversing in, or one they named explicitly (including a regional variant like en-us or en-gb) - so the returned profile is scoped to that language. Re-call this tool with the new `lang` if the user switches practice language or requests a specific variant mid-conversation.
user
get_user_profile
Profile snapshot: CEFR level, target/source languages, due card count, weak words, recent lookups. Pass `lang` to scope the snapshot to one learning language (for users learning several); omit it for the user's primary language.
words
check_words
Batch lookup: for a list of target-language words, tell me which ones are already in the user's Minddory deck and how well they know each. Use this BEFORE glossing or capturing vocabulary from a message - it answers "which of these are actually new to this user" in one call, so you can skip words they have already mastered, gloss only the genuinely new ones, and notice when a word they are currently failing shows up in conversation. Each result is {word, in_deck, mastery, translation, next_review_at, due}; mastery is one of not_in_deck, new, review, struggling, mastered. The response also pulls out the three lists you usually act on - `not_in_deck`, `known` and `struggling` - so you do not have to sort them yourself; words in mid-review are in `words` only. Entries that could not be answered as sent are listed in `skipped` as {input, reason: blank|duplicate, answered_as?} - a duplicate WAS answered, under the entry named by `answered_as`. Omit `lang` and it resolves to the user's own primary learning language (`lang_defaulted: true` in the response says so); pass it whenever you know which language you are in. Prefer this over calling get_card once per word.

Endpoints

URLTransportStateLatencyChecked
https://api.minddory.com/v1/brain/mcp streamable-http answering 305 ms 12 min ago

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MindDory Brain — questions

Answers built from our own checks of this server.

What can MindDory Brain do?
It exposes 13 tools, read directly from the server on our last check. Among them: capture_grammar_mistake, capture_word, check_words, get_active_vocab, get_card, get_known_words and 7 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
What is MindDory Brain mostly used for?
Its tools cluster around capture and mark. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.
Is MindDory Brain working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 428 ms. The bar chart above shows every period we have measured.
How do I connect MindDory Brain?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does MindDory Brain need an API key?
No. MindDory Brain completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 13 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is MindDory Brain?
It answers our handshake in 428 ms on average, which is faster than 35% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.
Is MindDory Brain open source?
Yes — it is published under the MIT licence and 0 stars on GitHub. The source link is on this page, so you can read exactly what it does with your data before you connect it.