vocabit-mcp
Allows sending a Telegram notification to the learner when a study set is waiting for them.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@vocabit-mcpCreate a flashcard set on Spanish food, then read back the weak cards."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
vocabit-mcp
An MCP server for Vocabit, a flashcard app. It lets an AI assistant write a study set into a real app on a real phone, and then read back how the learner actually did with it.
Most MCP servers read from an API. This one closes a loop:
flowchart LR
A["Assistant<br/>teaches a topic"] --> B["create_study_set"]
B --> C["Set appears in the<br/>Vocabit app"]
C --> D["Learner works<br/>through it"]
D --> E["get_set_results"]
E -->|weak cards| AThe interesting tool is not create_study_set — anything can generate flashcards.
It is get_set_results: which cards the learner marked hard, which they never reached,
how many reviews each one took. The next set is built out of that, not out of a guess.
Try it in 30 seconds
No backend, no account, no API key:
npx -y vocabit-mcp --demoDemo mode runs the same server against an in-memory Vocabit with two seeded sets. Create a set, ask for results, and a deterministic stand-in learner will have worked through it — flagged in the response as simulated, so it is never mistaken for real data.
To poke at it with a UI:
npx @modelcontextprotocol/inspector npx -y vocabit-mcp --demoInstall
Listed in the MCP Registry as io.github.JohnBilousov/vocabit-mcp, so clients that read the registry can find it on their own.
claude mcp add vocabit -- npx -y vocabit-mcp{
"mcpServers": {
"vocabit": {
"command": "npx",
"args": ["-y", "vocabit-mcp"],
"env": {
"VOCABIT_BASE_URL": "https://your-vocabit-backend.example.com",
"VOCABIT_AGENT_KEY": "your-agent-key"
}
}
}
}Drop the env block to run in demo mode.
Tools
Tool | What it does |
| Check the connection and which mode the server is in. |
| Publish a set to the learner's app. Returns a deep link that opens it on the device. |
| Recent sets, newest first, each with a progress summary. |
| Full contents of one set, plus the topic and notes the assistant attached. |
| The feedback half. Per-card status, |
| Retitle, retag, or append cards — typically the follow-up after reading results. |
| Telegram ping that a set is waiting. |
| Remove a set from the app. Study history is kept. |
Also exposed: the vocabit://set/{setId} resource (a set as JSON, listable) and a
study-session prompt that walks the whole loop.
Card states
Progress comes from the app's spaced-repetition engine, not from the assistant:
Status | Meaning |
| Never reviewed. |
| Learner marked it hard. |
| Marked good. |
| Marked easy. |
A set reports completed: true once no card is left in new.
Live mode
Point the server at a Vocabit backend that has the agent API enabled:
export VOCABIT_BASE_URL=https://your-vocabit-backend.example.com
export VOCABIT_AGENT_KEY=... # must match one of AGENT_API_KEYS on the backend
npx -y vocabit-mcpVariable | Purpose |
| Backend base URL. |
| Sent as |
| Firebase UID of the learner. Optional; the backend has a default. |
| Defaults for new sets, e.g. |
| Recipient for |
| Request timeout, default |
|
|
Set neither URL nor key and the server starts in demo mode. Set exactly one and it refuses to start — half a configuration is a mistake, not a hint.
Design notes
Demo mode is a first-class client, not a stub. HttpVocabitClient and
DemoVocabitClient implement the same VocabitClient interface, so no tool has a
branch for "are we pretending?". A reviewer can run the server before they have
credentials, and the test suite exercises the real tool surface over a real MCP
transport rather than mocking the SDK.
Errors are recoverable, not fatal. A failed call comes back as isError with the
backend's own message plus a hint aimed at the model — 404 says "call
list_study_sets to see which sets exist", 401 says "or run with VOCABIT_DEMO=1".
Mutually exclusive arguments are rejected with an explanation instead of a guess.
Output schemas stay loose on the edges. Identifying fields are required; everything else is optional, so a backend that grows a field does not turn a working tool into a validation error.
Annotations are honest. delete_study_set is marked destructiveHint, the read
tools readOnlyHint. notify_learner messages a real person, and its description says
to use it sparingly.
Development
git clone https://github.com/JohnBilousov/vocabit-mcp && cd vocabit-mcp
npm install
npm run build
npm test # tool surface + full loop over an in-memory MCP transport
npm run inspect # demo mode in the MCP Inspectorsrc/
index.ts CLI entry, stdio transport
config.ts env → Config, demo-mode resolution
server.ts tool / resource / prompt registration
schemas.ts zod input and output shapes
format.ts human-readable summaries next to structuredContent
client/
types.ts wire types + VocabitClient contract
http.ts live backend
mock.ts in-memory backend for demo modeRoadmap
Streamable HTTP transport alongside stdio
Multi-learner support without a backend default UID
Audio pronunciation cards
Publish to the MCP registry
License
MIT © Ivan Bilousov
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