- Read
PROMPT.md - Answer the Design Questions (write your answers directly in
PROMPT.md) - Build the prototype:
- Challenge Track: Build from scratch using
PROMPT.mdas your spec - Guided Track: Go to
scaffold/, fill in the TODOs
- Challenge Track: Build from scratch using
- Verify with the MCP inspector tests at the bottom of
PROMPT.md - Bring your Design Questions answers to live session for discussion
Challenge Track β You decide the architecture, file structure, and implementation. Any language with an MCP SDK works (Python + the official mcp SDK recommended). Read PROMPT.md to get started.
Guided Track β File structure and boilerplate are provided. Fill in the core logic marked with TODO. Go to scaffold/ and follow the instructions below.
cd scaffold
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txtYou also need Node.js for npx (used by the MCP inspector for verification).
| File | TODO | Design Decision |
|---|---|---|
app/scheduler.py |
get_time_bucket() + find_due_jobs() |
Time bucket partitioning for efficient job scanning |
app/mcp_server.py |
TOOL_REGISTRY + route_tool_call() |
Registry pattern for MCP tool routing |
The prototype is a real MCP stdio server. Verify with the MCP inspector (no Claude needed):
npx @modelcontextprotocol/inspector python -m app.mcp_serverThis opens a browser GUI β see PROMPT.md Verification section for the full test flow. Once the inspector tests pass, you can optionally connect to Claude Desktop / Claude Code (instructions also in PROMPT.md).
- Connect a real LLM to parse natural language task descriptions before calling
task.create - Add recurring job support (cron expressions)
- Add job chaining (Job A completes -> triggers Job B)
- Add MCP
resourcessupport (e.g., expose job details as readable resources) - Add MCP
promptssupport (e.g., adaily_reviewprompt template)