vocabit-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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": true
} |
| prompts | {
"listChanged": true
} |
| resources | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| vocabit_healthA | Verify the server can reach Vocabit and report which mode it is in (live backend or in-memory demo). Call this first if anything else fails. |
| create_study_setA | Build a flashcard set and publish it to the learner's Vocabit app. Returns a deep link that opens the set on their device. Prefer one focused topic and 8-15 cards per set — long sets get abandoned. Use the notes field for what you want to check afterwards; the learner never sees it. |
| list_study_setsA | List the sets you created for this learner, newest first, each with a progress summary. Use it to find a setId, or to see at a glance which sets were never opened. |
| get_study_setA | Read the full contents of a set — every card, plus the topic and notes you attached when you created it. |
| get_set_resultsA | Read back real study results for a set: which cards the learner marked hard (weakCards), which they never reached (untouchedCards), and per-card review counts. This is the feedback half of the loop — read it before writing the next set, and build the follow-up out of weakCards. |
| update_study_setA | Change a set in place: retitle it, retag it, or add cards. Pass addCards to append (the usual case after reviewing results) or cards to replace the list wholesale — never both. Replacing the cards resets what the learner has already studied. |
| notify_learnerA | Send the learner a Telegram message that a set is waiting. Use sparingly — one ping per set, right after you create it. |
| delete_study_setA | Remove a set from the learner's app. Study history is kept on the backend, but the set disappears from their device. Ask before calling this. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| study-session | Teach a topic, publish it as a set, and follow up on the last set's weak cards. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| Standup phrases for engineers | 5 cards · workplace english |
| Kirche & Glaube — Grundwortschatz | 8 cards · church vocabulary |
TDQS
Scored across 8 tools
Each tool has a clearly distinct purpose: health check, CRUD for study sets, results feedback, and learner notification. Even get_study_set and get_set_results are unambiguously separated—one retrieves content, the other study metrics. No two tools appear to do the same thing.
Most tools follow a verb_noun pattern (create_study_set, list_study_sets, update_study_set, delete_study_set, get_study_set, get_set_results). However, vocabit_health deviates from the verb-first style and notify_learner uses a non-set object, so the pattern is not perfectly uniform but remains predictable.
8 tools is well within the ideal 3-15 range and each earns its place in the set lifecycle. The count matches the server's scope—managing study sets with health check and notification—without redundancy or unnecessary bulk.
The tool surface covers the full lifecycle: create, read, update, delete, list, plus results feedback and learner notification. The feedback loop is closed by get_set_results informing update_study_set. Health check aids debugging. No obvious gaps that would cause agent failures.