studyos-mcp-server

An independent MCP (Model Context Protocol) server that bridges Claude Web to the StudyOS Problem Import API. It forwards batches of newly generated educational problems to StudyOS and returns a clear, structured result so Claude can decide whether to keep generating more.

Claude Web  ──▶  MCP (Streamable HTTP)  ──▶  studyos-mcp-server  ──▶  StudyOS Import API  ──▶  StudyOS Problem Bank

This project is not StudyOS. It does not contain a database, curriculum taxonomy, duplicate detection, or validation logic. StudyOS owns all of that. The MCP server only authenticates, forwards, retries transiently, and normalizes the response.

What it does (and does not do)

There is no database credential, Prisma, Supabase, or direct DB access in this project — by design.

Related MCP server: Canvas LMS MCP Server

The import_problems tool

Imports a batch of problems into the StudyOS Problem Bank.

Input

{
  "batchId": "claude-web-20260810-0001", // optional; auto-generated if omitted
  "source": "claude-web",                // optional; defaults to "claude-web"
  "targetNewProblems": 1000,             // optional; total NEW problems the whole job wants
  "problems": [                          // required; 1..500 per call
    {
      "gradeId": "elem-5",
      "subjectId": "math",
      "unitId": "fraction-mult",
      "difficulty": "medium",
      "type": "multiple_choice",
      "prompt": "3/4 × 2/5의 값은?",
      "choices": ["3/10", "2/5", "5/8", "6/20"],
      "answerText": "3/10",
      "explanation": "분자끼리 곱하고 분모끼리 곱합니다."
    }
  ]
}

• Max 500 problems per call. Larger jobs must be split into multiple calls.

• Reuse the same batchId only to retry the exact same batch (StudyOS handles idempotency). Use a fresh batchId for each new batch.

• Unknown extra fields on a problem are passed through to StudyOS untouched.

Output

{
  "ok": true,
  "batchId": "claude-web-20260810-0001",
  "received": 100,
  "accepted": 86,
  "duplicates": 12,
  "rejected": 2,
  "remaining": 914,
  "continueRecommended": true,
  "message": "Imported batch ...: 86 new, 12 duplicate, 2 rejected (of 100 received)."
}

• remaining is null when StudyOS does not report cumulative progress — in that case Claude tracks its own running total of accepted.

• continueRecommended is a hint for whether to generate another batch.

• On 400 / 401 / 403 / 422 the tool returns isError: true with a short message and does not retry. Transient failures (429 / 500 / 502 / 503 / 504 / network / timeout) are retried automatically with backoff, honoring Retry-After.

Configuration

All configuration is via environment variables. Never put the token in code, requests, logs, or git.

Copy .env.example to .env for local development (the real token goes in your host's secret manager, not in the repo).

Run locally

npm install
npm run build

# HTTP transport (what Claude Web connects to)
STUDYOS_IMPORT_TOKEN=<token> npm start
# -> http://localhost:3000/mcp   (health: GET http://localhost:3000/healthz)

# stdio transport (for MCP Inspector)
STUDYOS_IMPORT_TOKEN=<token> npm run start:stdio

Inspect with the official MCP Inspector:

npx @modelcontextprotocol/inspector

Deploy

The server speaks Streamable HTTP (stateless JSON) and needs a public HTTPS URL for Claude Web.

Option A — long-running Node host (Railway / Render / Fly / a container)

Build command npm run build, start command npm start. Set STUDYOS_IMPORT_TOKEN (and optionally STUDYOS_IMPORT_API_URL) as secrets. Claude Web connects to https://<host>/mcp.

Option B — Vercel (serverless)

This repo includes api/mcp.ts and vercel.json. Deploy to Vercel, set the env vars in the project settings, and Claude Web connects to:

https://<your-deployment>.vercel.app/api/mcp

Connect from Claude Web

1. Deploy the server and confirm GET /healthz returns { "ok": true }.

2. In Claude (web) → Settings → Connectors → Add custom connector.

3. Enter the MCP URL:

   • Node host: https://<host>/mcp

   • Vercel: https://<deployment>.vercel.app/api/mcp

4. Save. Claude can now call import_problems.

Then a user can simply ask, e.g.:

초5 수학 분수 단원 문제 1000개 만들어서 StudyOS 문제은행에 입고해줘.

Claude generates problems, calls import_problems in batches of ≤500, reads accepted / remaining, and repeats until the target of new problems is met.

Security

• The token is read lazily from the environment and is never logged, returned, or placed in error messages. A defensive redactor strips it from any string just in case.

• No database credentials are used or accepted (no DATABASE_URL, DIRECT_URL, SUPABASE_*, Prisma, or Postgres client).

• The server exposes exactly one tool (import_problems) and one upstream call (the StudyOS Import API) — no arbitrary request execution.

Testing

npm run typecheck   # tsc --noEmit
npm test            # vitest (schema, retry, normalization, redaction, tool e2e)
npm run build       # tsc

The suite covers: valid/empty/oversized/invalid batches, 401/403/422 no-retry, 429/500 retry with Retry-After, network + timeout handling, response normalization (partial success, duplicates, remaining, field-name variants), token redaction, and a full in-memory MCP client → tool round trip.

Project layout

studyos-mcp-server/
├── api/mcp.ts             # Vercel serverless entry (Option B)
├── vercel.json
├── src/
│   ├── index.ts           # entry: HTTP (default) + stdio transports
│   ├── server.ts          # createServer(): registers tools
│   ├── tools/importProblems.ts
│   ├── studyosClient.ts   # HTTP client: auth, retry, timeout, normalization, redaction
│   ├── schemas.ts         # Zod input schemas (basic shape check only)
│   ├── constants.ts       # config + retry policy
│   └── types.ts
└── test/                  # vitest suites