japanese-learning-memory
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| JAPANESE_LEARNING_MCP_DB | No | Path to the SQLite database file. If not set, defaults to data/japanese_learning.db in the project directory. |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| search_itemsC | Search personal Japanese knowledge items with optional filters. |
| upsert_itemC | Create or update an exact normalized-expression and item-type match. |
| add_relationA | Add a validated relation between two existing knowledge items. |
| record_mistakeB | Append one learning mistake without deduplicating history. |
| get_due_reviewsA | Return due reviews and new learning items; this query never mutates data. |
| submit_reviewA | Save review history, schedule the next review, and conservatively update mastery. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| review_today | Guide a focused daily review session. |
| analyze_confusion | Guide analysis of confusable Japanese expressions. |
| finish_speaking_session | Guide post-session speaking feedback and persistence. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| profile | Stable personal learning profile. |
| stats | Aggregate knowledge, mistake, due-review, and weakest-item statistics. |
| recent_mistakes | The 20 most recent learning mistakes. |
| due_today | Reviews due by the end of the current UTC day. |
TDQS
Scored across 6 tools
Each tool has a clearly distinct purpose: searching, upserting, relating, recording mistakes, fetching due reviews, and submitting reviews. No two tools overlap in function, and the descriptions reinforce their unique roles.
All tool names follow a consistent verb_noun pattern in snake_case (search_items, upsert_item, add_relation, record_mistake, get_due_reviews, submit_review). The verb is always first and the noun is always the object, creating a predictable and readable API.
With six tools, the server is well-scoped for a Japanese learning memory system. Each tool covers a distinct core operation without unnecessary bloat or thinning, fitting the typical 3-15 tool sweet spot.
The server covers the core lifecycle: create/update (upsert_item), read/search (search_items), relations (add_relation), and review scheduling (get_due_reviews, submit_review). A minor gap is the lack of an explicit delete operation, but this is not a fatal omission for a spaced-repetition memory system.