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  1. Home
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  3. Vocabit
  4. README

Vocabit README

The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Vocabit listing page.

Back to Vocabit View source on GitHub

vocabit-mcp

CI npm license

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:

mermaid
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| A

The 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:

Terminal
npx -y vocabit-mcp --demo

Demo 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:

Terminal
npx @modelcontextprotocol/inspector npx -y vocabit-mcp --demo

Install

Listed in the MCP Registry as io.github.JohnBilousov/vocabit-mcp, so clients that read the registry can find it on their own.

Claude Code
Terminal
claude mcp add vocabit -- npx -y vocabit-mcp
Claude Desktop / any MCP client
config.json
{
  "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

ToolWhat it does
vocabit_healthCheck the connection and which mode the server is in.
create_study_setPublish a set to the learner's app. Returns a deep link that opens it on the device.
list_study_setsRecent sets, newest first, each with a progress summary.
get_study_setFull contents of one set, plus the topic and notes the assistant attached.
get_set_resultsThe feedback half. Per-card status, weakCards, untouchedCards, due cards.
update_study_setRetitle, retag, or append cards — typically the follow-up after reading results.
notify_learnerTelegram ping that a set is waiting.
delete_study_setRemove 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:

StatusMeaning
newNever reviewed.
strugglingLearner marked it hard.
learningMarked good.
masteredMarked 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:

server.ts
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-mcp
VariablePurpose
VOCABIT_BASE_URLBackend base URL.
VOCABIT_AGENT_KEYSent as X-Agent-Key.
VOCABIT_USER_IDFirebase UID of the learner. Optional; the backend has a default.
VOCABIT_TERM_LANGUAGE / VOCABIT_DEFINITION_LANGUAGEDefaults for new sets, e.g. de / en.
VOCABIT_TELEGRAM_IDRecipient for notify_learner.
VOCABIT_TIMEOUT_MSRequest timeout, default 20000.
VOCABIT_DEMO1 forces demo mode.

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

bash
git clone https://github.com/JohnBilousov/vocabit-mcp && cd vocabit-mcp
npm install
npm run build
npm test          # tool surface + full loop, plus the HTTP client against a mocked fetch
npm run lint      # eslint
npm run format    # prettier --write
npm run inspect   # demo mode in the MCP Inspector

CI runs typecheck, lint, format:check, test, and build on every push and pull request.

Code
src/
  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 mode
test/
  server.test.ts       tool surface + full loop — over an in-memory MCP transport
  client/
    http.test.ts       query encoding, error-body parsing, timeouts — against a mocked fetch

Releasing

Publishing uses npm's trusted publishing (OIDC) — no NPM_TOKEN secret, nothing that can leak or expire. One-time setup on npmjs.com, under the package's Settings → Trusted publishing → GitHub Actions: organization JohnBilousov, this repository, workflow filename publish.yml.

To cut a release: bump the version in package.json, server.json, and VERSION in src/server.ts together (a test asserts they can't drift), commit, push, then publish a GitHub Release with a matching vX.Y.Z tag. That triggers .github/workflows/publish.yml, which runs the test suite and publishes to npm with provenance — the package page shows a verified link back to this exact commit and workflow run, not just a name on the registry.

Roadmap

  • Streamable HTTP transport alongside stdio
  • Multi-learner support without a backend default UID
  • Audio pronunciation cards

License

MIT © Ivan Bilousov