Stonks
README.md
# 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.
## š 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. **š° News Analysis + Market Context** (Column D)
- Company-specific news and earnings
- Broader market trends and economic factors
- Geopolitical impact and industry disruption
2. **š¤ AI-Powered Insights** (Column E)
- Predictive modeling and pattern recognition
- Scenario analysis with probability assessments
- Market timing indicators
3. **š Investor Insights** (Column F)
- Technical and fundamental analysis
- Risk assessment and competitive analysis
- Sector dynamics and catalyst calendar
4. **š° Quick Financials Overview** (Column G)
- Key financial metrics and ratios
- Growth rates and profitability analysis
- Liquidity and valuation metrics
5. **š¢ Institutional Information** (Column H)
- Institutional ownership data
- Hedge fund and mutual fund activity
- Insider trading and analyst coverage
## š 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](https://developers.google.com/workspace/sheets/api/quickstart/python)**
### 2. Installation
```bash
# 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:
```env
GOOGLE_API_KEY=your_gemini_api_key
SPREADSHEET_ID=your_google_sheets_id
RANGE_NAME=Sheet1!A6:C9
```
### 4. Usage
#### Option A: Standalone Mode
```bash
# 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:
```json
{
"mcpServers": {
"stonks-server": {
"command": "path to your python bin",
"args": ["path to server.py"]
}
}
}
```
**Note**: Update the paths to match your actual installation directory.
## šÆ 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
## š 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.)
## š§ 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
## š Sample Workflow
```
User: "Update all stocks with latest news and analysis"
ā
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
```
## šØ 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
## š Future Enhancements
- Real-time data integration
- Advanced charting capabilities
- Portfolio performance tracking
- Custom analysis templates
- Multi-exchange support
---
**Setup Guide**: [Google Sheets API Quickstart](https://developers.google.com/workspace/sheets/api/quickstart/python)This server cannot be deployed
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