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Areeburrehman-26

time-left-mcp-chatgpt

by Areeburrehman-26
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Python
Remote

Preview

Time Left - ChatGPT App

A simple ChatGPT app that shows elegant progress bar visualizations of how much time is left in the current day, week, month, and year.

Features

  • Single Tool: get_time_remaining - answers "how much time is left?" queries

  • Visual Progress Bars: Animated, color-coded bars for each time period

  • Light/Dark Theme: Automatically matches ChatGPT's theme

  • Real-time Calculation: Shows current elapsed/remaining percentages

Quick Start

# Install dependencies
uv sync

# Run the server
uv run python server/main.py

The server will start on http://localhost:8000.

Running Tests

# Install dev dependencies
uv sync --all-extras

# Run all tests
uv run pytest

# Run tests with verbose output
uv run pytest -v

# Run a specific test
uv run pytest server/test_main.py::TestCalculateTimeRemaining::test_noon_day_progress_is_fifty -v

Testing with MCP Inspector

npx @modelcontextprotocol/inspector@latest http://localhost:8000/mcp

Note: MCP Inspector tests the protocol but doesn't render the widget UI. Use web/preview.html to preview the widget locally.

Testing in ChatGPT (with Cloudflare Tunnel)

ChatGPT needs a public HTTPS URL to connect to your MCP server. Cloudflare Tunnel provides this for free without an account.

1. Install Cloudflare Tunnel (one-time)

# macOS
brew install cloudflared

# Or download from https://developers.cloudflare.com/cloudflare-one/connections/connect-apps/install-and-setup/installation/

2. Start the server and tunnel

# Terminal 1: Start the MCP server
uv run python server/main.py

# Terminal 2: Create a tunnel to localhost:8000
cloudflared tunnel --url http://localhost:8000

Cloudflare will output a URL like:

Your quick Tunnel has been created! Visit it at:
https://random-words-here.trycloudflare.com

3. Configure ChatGPT

  1. Go to ChatGPT: Settings → Apps & Connectors → Advanced settings

  2. Enable Developer mode

  3. Click Create connector

  4. Enter the Cloudflare URL with /mcp path: https://random-words-here.trycloudflare.com/mcp

  5. Save the connector

4. Test it

Ask ChatGPT: "How much time is left?" or "What's my time progress?"

Local Widget Preview

To preview the widget without ChatGPT:

  1. Start the server: uv run python server/main.py

  2. Open web/preview.html in a browser

This preview mocks the window.openai API that ChatGPT normally provides.

Project Structure

time-left-chatgpt-app/
├── server/
│   ├── main.py           # MCP server with get_time_remaining tool
│   ├── test_main.py      # Unit tests
│   └── requirements.txt  # Legacy deps (use pyproject.toml instead)
├── web/
│   ├── widget.html       # Progress bar visualization widget
│   └── preview.html      # Local preview with mocked window.openai
├── pyproject.toml        # Project config and dependencies
└── README.md

Architecture

User Prompt → ChatGPT Model → MCP Tool Call → This Server → Response + Widget Metadata
                                                              ↓
                                           ChatGPT loads widget.html in iframe
                                                              ↓
                                           Widget reads from window.openai.toolOutput

Key data flow:

  • structuredContent in server response → window.openai.toolOutput in widget

  • _meta contains OpenAI directives only (openai/outputTemplate, etc.)

Production Deployment

For production deployment to Google Cloud Run (or similar), the server includes:

CSP Configuration

The tool metadata includes Content Security Policy settings required for ChatGPT app submission:

"openai/widgetCSP": {
    "connect_domains": [],      # Empty - widget doesn't make external API calls
    "resource_domains": [],     # Empty - all assets are inline
},
"openai/widgetDomain": WIDGET_DOMAIN

Environment Variables

Variable

Default

Description

PORT

8000

Server port (Cloud Run sets this automatically)

WIDGET_DOMAIN

https://web-sandbox.oaiusercontent.com

Widget execution domain

Deploying to Google Cloud Run

# Build and deploy
gcloud run deploy time-left \
  --source . \
  --region us-central1 \
  --allow-unauthenticated \
  --set-env-vars WIDGET_DOMAIN=https://your-domain.com

# Map custom domain
gcloud run domain-mappings create \
  --service time-left \
  --domain your-domain.com \
  --region us-central1

App Submission Checklist

  • CSP configured (openai/widgetCSP)

  • Widget domain configured (openai/widgetDomain)

  • Organization verified on OpenAI Platform

  • Production URL deployed and accessible

  • Privacy policy URL prepared

Submit at: https://platform.openai.com/apps-manage

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