Stonks

Pbonmars-20031006/Stonks

3.2

If you are the rightful owner of Stonks and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to henry@mcphub.com.

An intelligent MCP server that automates stock analysis and news updates in Google Sheets using AI-powered insights.

Tools
  1. initialize

    Set up Google Sheets authentication.

  2. get_stocks

    Fetch stock data from spreadsheet.

  3. update

    Add analysis to specific cells with multiple analysis types.

  4. search_news

    Generate news summaries using Gemini AI.

  5. plot_institutional_chart

    Create ownership visualization charts.

Stock News Automation Service

An intelligent MCP (Model Context Protocol) server that automates stock analysis and news updates in Google Sheets using AI-powered insights.

šŸš€ Features

Core Capabilities

  • Google Sheets Integration: Seamlessly connects to your Google Sheets for real-time stock data management
  • AI-Powered Analysis: Uses Google Gemini to generate comprehensive stock analysis
  • Multi-Type Analysis: Supports 5 different analysis types for comprehensive coverage
  • Institutional Data Visualization: Creates charts for institutional ownership data
  • Automated News Updates: Fetches and summarizes latest stock news

Analysis Types Available

  1. šŸ“° News Analysis + Market Context (Column D)

    • Company-specific news and earnings
    • Broader market trends and economic factors
    • Geopolitical impact and industry disruption
  2. šŸ¤– AI-Powered Insights (Column E)

    • Predictive modeling and pattern recognition
    • Scenario analysis with probability assessments
    • Market timing indicators
  3. šŸ“Š Investor Insights (Column F)

    • Technical and fundamental analysis
    • Risk assessment and competitive analysis
    • Sector dynamics and catalyst calendar
  4. šŸ’° Quick Financials Overview (Column G)

    • Key financial metrics and ratios
    • Growth rates and profitability analysis
    • Liquidity and valuation metrics
  5. šŸ¢ Institutional Information (Column H)

    • Institutional ownership data
    • Hedge fund and mutual fund activity
    • Insider trading and analyst coverage

šŸ› ļø Setup Instructions

Prerequisites

  • Python 3.8+
  • Google Cloud Console account
  • Google Sheets API access

1. Google Sheets API Setup

Follow the official Google guide to set up API access: Google Sheets API Quickstart

2. Installation

# Clone the repository
git clone <your-repo-url>
cd stocks

# Create virtual environment
python -m venv stocks
source stocks/bin/activate  # On Windows: stocks\Scripts\activate

# Install dependencies
pip install -r requirements.txt

3. Configuration

  1. Download credentials.json from Google Cloud Console
  2. Place it in the project root directory
  3. Create .env file with:
GOOGLE_API_KEY=your_gemini_api_key
SPREADSHEET_ID=your_google_sheets_id
RANGE_NAME=Sheet1!A6:C9

4. Usage

Option A: Standalone Mode
# Start the MCP Server
python server.py

# Run the Client
python client.py server.py
Option B: MCP Client Integration

Add to your MCP client configuration:

{
  "mcpServers": {
    "stonks-server": {
      "command": "path to your python bin",
      "args": ["path to server.py"]
    }
  }
}

Note: Update the paths to match your actual installation directory.

šŸŽÆ How It Works

  1. Initialize: Authenticate with Google Sheets API
  2. Get Stocks: Retrieve stock data from your spreadsheet
  3. Analyze: Generate AI-powered analysis for each stock
  4. Update: Automatically populate analysis in designated columns
  5. Visualize: Create institutional ownership charts

šŸ“‹ Available MCP Tools

  • initialize(): Set up Google Sheets authentication
  • get_stocks(): Fetch stock data from spreadsheet
  • update(): Add analysis to specific cells with multiple analysis types
  • search_news(): Generate news summaries using Gemini AI
  • plot_institutional_chart(): Create ownership visualization charts

These tools are available through any MCP-compatible client (Claude Desktop, etc.)

šŸ”§ Technical Architecture

  • MCP Server: FastMCP framework for tool orchestration
  • AI Integration: Google Gemini for intelligent analysis
  • Data Visualization: Matplotlib for institutional charts
  • Authentication: OAuth2 for secure Google Sheets access
  • Client Interface: LangGraph with React agent for natural language interaction

šŸ“Š Sample Workflow

User: "Update all stocks with latest news and analysis"
↓
Agent: 
1. Initializes Google Sheets connection
2. Retrieves stock symbols from spreadsheet
3. Generates news analysis for each stock
4. Updates respective columns with AI insights
5. Creates institutional ownership charts

🚨 Important Notes

  • Analysis is based on last 10 days of data
  • Includes references to SeekingAlpha, TradingTerminal, and TradingView
  • Not financial advice - for informational purposes only
  • Requires valid Google API credentials

šŸ“ˆ Future Enhancements

  • Real-time data integration
  • Advanced charting capabilities
  • Portfolio performance tracking
  • Custom analysis templates
  • Multi-exchange support

Setup Guide: Google Sheets API Quickstart