MMPSMulti-Purpose Telegram Bots

Quick Links ​

• Getting Started - Set up MMPS in 5 minutes
• Architecture - Understand the system design
• Available Bots - Explore all 6 bots and their features
• Contributing - Help improve MMPS
• Deployment - Deploy to production

Tech Stack ​

• Node.js 24.x - Runtime
• TypeScript 5.9 - Type-safe development
• MongoDB - Data persistence
• grammY - Telegram bot framework
• LangChain + LangGraph - AI orchestration
• OpenAI & Anthropic - Large language models

Project Overview ​

MMPS is a multi-purpose Telegram bot platform built with plain TypeScript and Node.js. Each bot operates independently with its own database, services, and scheduled tasks. The application uses manual dependency injection for simplicity and control, with no external frameworks overhead.

The 6 Bots ​

1. Chatbot - AI-powered conversational assistant with advanced features
2. Coach - Sports predictions and analytics with real-time data
3. Langly - Language learning companion with daily challenges
4. Magister - Course management and lesson reminders
5. Wolt - Restaurant availability notifications
6. Worldly - Geography education and trivia challenges

Get Started ​

# Clone the repository
git clone https://github.com/matansocher/mmps
cd mmps

# Install dependencies
npm install

# Set up environment variables
cp .env.example .env
# Edit .env with your credentials

# Run in development
npm run start:dev

# Or run a specific bot
LOCAL_ACTIVE_BOT_ID=chatbot npm run start:dev

For detailed setup instructions, see the Getting Started Guide.

Documentation Structure ​

• Guide - Installation, configuration, and getting started
• Architecture - System design, patterns, and code guidelines
• Bots - Detailed documentation for each of the 6 bots
• Development - Contributing guidelines, testing, and extending the platform
• Deployment - Production deployment and monitoring

License ​

This project is licensed under the MIT License.

Search Documentation ​

Use the search feature to quickly find information across all documentation:

• Desktop: Press Cmd+K (Mac) or Ctrl+K (Windows/Linux)
• Mobile: Tap the search icon in the header
• Search across all pages, guides, bot documentation, and examples