bunpro-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| VAULT_PATH | Yes | Path to the Obsidian vault folder (or any directory) where notes are stored. Use an absolute path. |
Capabilities
Features and capabilities supported by this server
| 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 |
|---|---|
| get_review_queueA | Get the Japanese items most in need of review right now, ordered by priority. Call this at the start of a review session. Returns grammar points and vocabulary with a freshness score for each, plus a note on how the learner last got it wrong. |
| get_practice_poolA | Get a pool of Japanese words and grammar the learner has ALREADY mastered, for active-use practice — the opposite of the review queue. Use this when the learner wants to be tested on or practice words they already know, not review what they're forgetting. Workflow: (1) ideate a concrete conversation theme or scenario (ordering at an izakaya, complaining about the weather, a job interview); (2) call this to get the mastered pool; (3) the pool is NOT pre-filtered by theme — from it, you pick the words and grammar that fit your theme, using each item's meaning; (4) propose the scenario and your chosen words to the learner and get their buy-in before starting; (5) run the practice conversation; (6) at the end, call submit_grades once for every item you practiced — grade fluent use 3 or 4, hesitation 2, and a blank or misuse 1 with a one-sentence error_note. Returns each item with its meaning and reading so you can select by theme. |
| get_itemA | Get everything known about one Japanese grammar point or word, including the learner's own notes from their vault. |
| submit_gradesA | Record how the learner performed on items during a review. Call this at the END of a review session, once, with every item you observed. Grade 1 = could not recall or used it wrong, 2 = struggled, 3 = correct, 4 = effortless. Include a one-sentence error_note when they got it wrong, describing the specific mistake. |
| add_itemA | Add a Japanese grammar point or word the learner has just
encountered. Fill in the reading, meaning, and JLPT level yourself from
your own knowledge of Japanese — do not ask the learner for them unless
the word is genuinely ambiguous. Put any context the learner gave you
(where they met it, what confused them) into |
| import_exportA | Import a Bunpro CSV export into the vault. ALWAYS run with dry_run=true first and show the learner the report before running for real. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
Latest Blog Posts
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/Muslinmin/Japanese_MCP'
If you have feedback or need assistance with the MCP directory API, please join our Discord server