Toddle Timetable MCP Server

A minimal Model Context Protocol server that lets Claude look up a student's daily class schedule. It speaks the Streamable HTTP transport, so it can be added to Claude as a custom connector.

Ships with a built-in mock timetable — no API credentials needed to try it.

Tool

Tool	Input	Output
get_daily_timetable	date — a day formatted YYYY-MM-DD	Markdown summary, one line per period (09:00 — Mathematics (Room 2B, Ms. Rao))

Weekends and dates listed in DATE_OVERRIDES return a "no classes scheduled" message. A malformed date returns a hint rather than raising.

Run locally

Requires Python 3.10+ (FastMCP does not support 3.9).

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
python server.py

The server listens on http://0.0.0.0:8000/mcp. Override with the HOST and PORT environment variables. GET / returns a small JSON health payload.

Use the endpoint URL with no trailing slash. /mcp/ answers with a 307 redirect to /mcp; some clients will not replay a POST body across a redirect. Always give clients exactly .../mcp.

Authentication

There is none, by design. No auth provider is configured, so the server never returns 401, never sends a WWW-Authenticate header, and serves no OAuth metadata — the /.well-known/oauth-* paths all return 404. Any MCP client can connect anonymously.

That also means anyone with the URL can call the tool. Fine for mock data; add FastMCP auth before wiring in real student records.

Verify it's up

npx @modelcontextprotocol/inspector

Point the inspector at http://localhost:8000/mcp, transport Streamable HTTP, then call get_daily_timetable with {"date": "2026-08-10"}.

Connect to Claude

Settings → Connectors → Add custom connector → URL http://localhost:8000/mcp. For Claude on the web the URL must be publicly reachable — deploy it (below) or tunnel with ngrok http 8000.

Swapping in real data

Everything mock-specific lives in two places in server.py:

• WEEKLY_TIMETABLE / DATE_OVERRIDES — the sample data.
• fetch_timetable(day) — the single seam the tool calls.

Replace the body of fetch_timetable with your API call and keep the return shape: a list of {"time", "subject", "room", "teacher"} dicts. Read credentials from the environment, never hard-code them:

import os, requests

def fetch_timetable(day):
    resp = requests.get(
        "https://api.example.com/timetable",
        params={"date": day.isoformat()},
        headers={"Authorization": f"Bearer {os.environ['TODDLE_API_TOKEN']}"},
        timeout=10,
    )
    resp.raise_for_status()
    return sorted(resp.json()["entries"], key=lambda e: e["time"])

Deploy

The server reads PORT from the environment and binds 0.0.0.0, which is what most PaaS providers expect.

Render

New → Web Service → point at this repo, then:

• Build command: pip install -r requirements.txt
• Start command: python server.py

Render injects PORT automatically. A Procfile is included for platforms that use one (Railway, Heroku). Your connector URL is https://<your-service>.onrender.com/mcp.

Fly.io / containers

FROM python:3.12-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY server.py .
CMD ["python", "server.py"]

A note on Vercel

Vercel's Python runtime is serverless and request-scoped, which doesn't fit a long-lived Streamable HTTP MCP session cleanly. Prefer Render, Railway, or Fly.io. If you must use Vercel, use their mcp-handler adapter rather than server.py as-is.

Project layout

server.py          # MCP server, mock provider, and the get_daily_timetable tool
requirements.txt   # fastmcp, requests, uvicorn
Procfile           # start command for PaaS deploys