OpenBB Widgets JSON MCP Server

# Monte Carlo Stock Simulation Widget A self-contained OpenBB widget that performs Monte Carlo simulations for stock price forecasting. <img width="730" height="1772" alt="image" src="https://github.com/user-attachments/assets/ef9e72e6-9bc1-4469-8e56-525934dfb756" /> Created with Claude Code and the prompt _"Create an OpenBB widget that has 3 parameters (ticker str, start date and boolean). The data is meant to be a plotly chart, but also support raw data. And because it's a monte carlo simulation, can you add a run button to it?"_. ## Features - **3 Parameters:** - `ticker` (text): Stock symbol (e.g., AAPL, MSFT) - `start_date` (date): Historical data start date for analysis - `use_volatility_adjustment` (boolean): Apply volatility adjustment to simulation - **Dual Output Modes:** - **Chart Mode** (default): Interactive Plotly visualization showing simulation paths and percentiles - **Raw Data Mode**: Pure simulation data arrays (1000 simulations × 253 days each) - **Run Button**: Manual execution control for Monte Carlo simulations ## Installation & Setup 1. **Install dependencies with uv:** ```bash cd playground uv sync ``` 2. **Run the widget server:** ```bash uv run python main.py ``` 3. **Access the widget:** - Server runs on `http://localhost:8000` - Widget configuration: `http://localhost:8000/widgets.json` - Widget endpoint: `http://localhost:8000/monte_carlo_simulation` ## Usage ### Chart Mode (Default) ``` GET /monte_carlo_simulation?ticker=AAPL&start_date=2023-01-01&use_volatility_adjustment=false ``` ### Raw Data Mode ``` GET /monte_carlo_simulation?ticker=AAPL&start_date=2023-01-01&use_volatility_adjustment=false&raw=true ``` ## Widget Configuration The widget is automatically registered with OpenBB Workspace and includes: - Type: chart (plotly) - Grid size: 40×15 - Run button enabled - Raw data toggle enabled - Category: Finance/Analysis - All parameters configurable in UI ## Monte Carlo Simulation Details - Fetches historical stock data using yfinance - Calculates daily returns and volatility - Runs 1000 simulations over 252 trading days (1 year) - Volatility adjustment reduces mean return by 20% and increases volatility by 20% - Chart shows 50 simulation paths plus 5th, 25th, 50th, 75th, and 95th percentiles - Raw data returns pure simulation arrays (1000 simulations × 253 price points each)