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Capture vocabulary and grammar from AI conversations into spaced-repetition flashcards for language learning.
Do not connect
A critical issue was found. Do not connect this server as-is.
Scanned 28 days ago Due for re-check
A server can change after it's graded. Re-run the automated scan to refresh this report.
This grade is deterministic and reproducible: the same server surface always yields the same grade under a given algorithm version. It is a real automated assessment computed by the MCPGrade engine from what the probe actually observed — not a fabricated or opinion score. It is not a manual human pentest, so it can miss context-specific risks.
Every signal below was measured directly by the automated probe. The grade is derived only from evidence like this — nothing is assumed.
The minddory-brain MCP server exposes 13 tools, focused primarily on general-purpose capabilities. Its published description reads: "Capture vocabulary and grammar from AI conversations into spaced-repetition flashcards for language learning". It communicates over Streamable HTTP using the 2026-07-28 protocol revision, and does not require authorization to connect. MCPGrade currently rates minddory-brain F — a critical issue was found and the server should not be connected as-is. Its most notable findings include "Data-exfiltration parameters" and "Data-exfiltration parameters". This report is a deterministic, reproducible automated assessment: the same observed surface always yields the same grade under a given algorithm version, and it is refreshed as new scans arrive and free to read — but it is not a substitute for a manual human security review. Always re-check minddory-brain's advertised tools, transport security, and authorization posture before connecting an autonomous agent or sharing sensitive context with it.
Add minddory-brain to an MCP client using the endpoint below. Review the grade and findings above before granting an autonomous agent access.
MCP endpoint
https://api.minddory.com/v1/brain/mcpStreamable HTTP transport. This is the MCP endpoint, not a website — paste it into your MCP client server list rather than a browser.
Captured passively during the read-only scan. Click any value to find servers that match it.
The tools this server advertises via tools/list — names, purposes, and the parameters each accepts, exactly as enumerated read-only.
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
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
Words the user has verified known via flashcard practice. Paginated keyset on flashcards.id.
Sorted worst-first. Each finding shows its severity, what it means, its OWASP MCP Top-10 mapping, and a recommended fix — the check id links to the exact methodology row that produced it.
tool: mark_demonstrated
A tool exposes a free-text/webhook/feedback parameter with no honest purpose — a classic exfil channel.
parameter "context"RecommendationRemove side-channel parameters; constrain tool inputs.
tool: mark_struggled
A tool exposes a free-text/webhook/feedback parameter with no honest purpose — a classic exfil channel.
parameter "context"RecommendationRemove side-channel parameters; constrain tool inputs.
tool: capture_word
A tool exposes a free-text/webhook/feedback parameter with no honest purpose — a classic exfil channel.
deck from real conversations, so use this proactively to log notable targetRecommendationRemove side-channel parameters; constrain tool inputs.
tool: capture_grammar_mistake
A tool description tries to alter the model’s use of another tool.
) - get it from get_system_instructions on first turn. Before logging, check that the "RecommendationDescriptions must describe only their own tool.
tool: get_active_vocab
A tool description tries to alter the model’s use of another tool.
capture_word + log_interaction events), ranked by frequency over a lookback wiRecommendationDescriptions must describe only their own tool.
tool: check_words
A tool description tries to alter the model’s use of another tool.
is over calling get_card once per word.RecommendationDescriptions must describe only their own tool.
The server accepts tool enumeration (and likely invocation) with no authentication.
RecommendationRequire OAuth 2.1 authorization for any server exposing non-public tools.
Vantaj uptime monitoring via MCP — manage monitors, heartbeats, incidents, and status pages.
Unified gateway to Algeria's TKAWEN ecosystem: commerce, certification, and AI tools.
Provides access to the Cohereon Doctrine AI safety framework with governance components, tiered access, and agent onboarding.
Agentic rails for complex workflows with receipts, fees, and MCP tool access.
Structural TC39 spec lookup for ECMA-262 and ECMA-402 in AI agents, SHA-pinned and offline-first.
Structural TC39 spec lookup for ECMA-262 and ECMA-402 in AI agents, SHA-pinned and offline-first.
Cards due now and due within the next 24 hours.
Single card detail by word (case-insensitive). Returns translation, mastery, and last 10 events.
Event log slice with optional surface filter and keyset pagination on answers.id.
Append a generic interaction event to the answers log. Use for lookups, AI discussions, and reading-in-context signals.
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.
Spaced-repetition degrade for a word the user just got wrong: the card comes back sooner. ease_factor drops, interval resets, repetitions reset.
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 M
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, c
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 k
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 messa