What is Bull Vision Agent

Bull Vision Agent is a FastAPI application that integrates with Telegram using webhooks and the OpenAI Agents SDK to provide AI-powered stock trading assistance. It utilizes MCPHub for managing multiple MCP servers.

Use cases

Use cases for Bull Vision Agent include automated stock trading assistance, real-time stock market analysis, volume wall detection, stock news analysis, and providing users with conversational trading support through Telegram.

How to use

To use Bull Vision Agent, clone the repository, install the dependencies using ‘poetry install’, and configure the environment variables in the .env file with your Telegram bot token, webhook URL, server settings, and Azure OpenAI API credentials.

Key features

Key features include Telegram bot integration with webhook support, AI-driven stock analysis, multiple MCP server integration via MCPHub, real-time stock data analysis, market news integration, conversation history tracking, trading context management, and MongoDB integration for data persistence.

Where to use

Bull Vision Agent can be used in financial sectors, particularly in stock trading and investment analysis, where real-time data and AI assistance can enhance decision-making.

Bull Vision Agent

A FastAPI application that integrates with Telegram using webhooks and OpenAI Agents SDK for AI-powered stock trading assistance, utilizing MCPHub for multiple MCP server management.

Features

• Telegram bot integration with webhook support
• AI-powered stock analysis using OpenAI Agents SDK
• Multiple MCP server integration via MCPHub:
  • Stock news analysis
  • Volume wall detection
• Real-time stock data analysis
• Market news integration
• Conversation history tracking
• Trading context management
• MongoDB integration for data persistence

Project Structure

├── app/
│   ├── __init__.py
│   ├── main.py           # FastAPI app with MCPHub initialization
│   ├── api/
│   │   ├── __init__.py
│   │   └── telegram_webhook.py  # Telegram webhook endpoint
│   ├── bot/
│   │   ├── __init__.py
│   │   ├── bot.py            # Bot instance and context management
│   │   ├── agent.py          # AI agent implementation with MCP servers
│   │   ├── context.py        # Conversation context and history
│   │   └── telegram_handler.py  # Process incoming messages
│   ├── core/
│   │   ├── __init__.py
│   │   └── settings.py   # Application settings
│   ├── models/
│   │   ├── __init__.py
│   │   └── news.py           # News data models
│   ├── services/
│   │   ├── __init__.py
│   │   └── mongodb_service.py # MongoDB operations
│   └── startup.py        # Startup events

Setup

1. Clone the repository

2. Install dependencies:

   poetry install
   

3. Copy .env.example to .env and fill in the required values:

   cp .env.example .env
   

4. Edit .env with your actual values:

   • TELEGRAM_BOT_TOKEN: Your Telegram bot token from @BotFather
   • TELEGRAM_WEBHOOK_URL: The public URL where your bot will receive updates
   • HOST and PORT: Server configuration
   • AZURE_OPENAI_API_KEY: Your Azure OpenAI API key
   • AZURE_OPENAI_ENDPOINT: Your Azure OpenAI endpoint
   • AZURE_OPENAI_DEPLOYMENT: Your Azure OpenAI deployment name
   • AZURE_OPENAI_API_VERSION: Azure OpenAI API version
   • MONGO_URI: MongoDB connection string
   • MONGO_DB: MongoDB database name

Running the Application

Start the server:

make run

Webhook Setup

1. Make sure your server is publicly accessible
2. The webhook URL should be in the format: https://your-domain.com/api/telegram/webhook
3. The webhook will be automatically registered when the application starts

Available Commands

• /start - Start the bot
• /help - Show help message

Example Queries

You can ask the bot about:

• Stock analysis (e.g., “Analyze AAPL”)
• Market news (e.g., “What’s the latest news about Tesla?”)
• Trading strategies (e.g., “What’s your view on the current market?”)
• Volume analysis (e.g., “Check volume patterns for MSFT”)

Development Commands

make install    # Install dependencies
make run       # Run the application
make test      # Run tests
make lint      # Run linters
make format    # Format the code
make clean     # Clean up generated files
make setup     # Setup development environment
make check     # Run all checks

Documentation

For detailed instructions on:

1. Setting up the AI Chatbot with Telegram and OpenAI Agents SDK, see init_telegram_openai_agent.md
2. Using MCPHub with multiple MCP servers, see create_telegram_chatbot_multi_mcp_server.md