shirshak-dugtal/mcp
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A Model Context Protocol (MCP) server for Indian stock market analysis providing real-time market data, technical analysis, options analytics, and portfolio management using 100% free APIs.
概要
A Model Context Protocol (MCP) server for Indian stock market analysis providing real-time market data, technical analysis, options analytics, and portfolio management using 100% free APIs. IndiaQuant MCP provides 11 tools for NSE/BSE market analysis: - Live market data (prices, volume, percentage changes) - Technical analysis (RSI, MACD, Bollinger Bands) - Options analytics (Black-Scholes Greeks calculated from scratch) - Sentiment analysis (news-based scoring with NewsAPI + TextBlob) - Market scanning (NIFTY 50 overbought/oversold detection) - Portfolio management (virtual trading with P&L tracking) - Sector analysis (IT, Banking, Auto, Pharma, FMCG heatmaps) - Each module handles a specific domain (market data, signals, options, etc.
README
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IndiaQuant MCP Server
A Model Context Protocol (MCP) server for Indian stock market analysis providing real-time market data, technical analysis, options analytics, and portfolio management using 100% free APIs.
Overview
IndiaQuant MCP provides 11 tools for NSE/BSE market analysis:
- Live market data (prices, volume, percentage changes)
- Technical analysis (RSI, MACD, Bollinger Bands)
- Options analytics (Black-Scholes Greeks calculated from scratch)
- Sentiment analysis (news-based scoring with NewsAPI + TextBlob)
- Market scanning (NIFTY 50 overbought/oversold detection)
- Portfolio management (virtual trading with P&L tracking)
- Sector analysis (IT, Banking, Auto, Pharma, FMCG heatmaps)
Architecture
Module Structure
IndiaQuant/
├── server.py # MCP server entry point (stdio transport)
├── market_data/
│ └── fetcher.py # Live NSE/BSE price fetching (yfinance)
├── trading_signals/
│ └── signal_generator.py # RSI, MACD, Bollinger Bands (pandas-ta)
├── options_analysis/
│ ├── options_analyzer.py # Options chain data (yfinance)
│ ├── greeks.py # Black-Scholes Greeks implementation
│ └── unusual_activity.py # Volume/OI spike detection
├── utils/
│ ├── sentiment.py # News sentiment analysis
│ └── market_scanner.py # NIFTY 50 scanner, sector heatmap
├── portfolio_management/
│ └── portfolio_manager.py # Virtual portfolio with SQLite
└── database/
└── portfolio.db # SQLite database
Design Decisions
1. Modular Architecture
- Each module handles a specific domain (market data, signals, options, etc.)
- Clean separation of concerns for maintainability
- Easy to extend with new tools
2. 100% Free API Stack
- yfinance: Live NSE/BSE prices, historical data (unlimited, free)
- NewsAPI: News headlines for sentiment (100 requests/day free tier)
- pandas-ta: Technical indicators (open source)
- TextBlob: Sentiment scoring (open source)
- Custom Black-Scholes: Greeks calculation from scratch
3. MCP Protocol Implementation
- Stdio transport for maximum compatibility
- Proper tool registration with JSON schemas
- Type-safe parameter validation
- Structured error handling
Trade-offs & Limitations
What Works:
- Live NSE/BSE stock prices for all securities
- Technical indicators (RSI, MACD, Bollinger Bands)
- Greeks calculation for any stock option
- News sentiment analysis
- Portfolio tracking with real-time P&L
- Sector performance analysis
Known Limitations:
- NSE Options Chain Data: yfinance has limited support for NSE options chains. Works reliably for US stocks but inconsistent for Indian stocks due to Yahoo Finance’s data coverage. For production, would use NSE Official API or broker APIs (Zerodha, Angel One).
- NewsAPI Rate Limits: Free tier allows 100 requests/day
- Index Options: NIFTY/BANKNIFTY index options not supported via yfinance
インストール
This server does not publish a one-line install command.
Open the repository installation guide MCP 初心者？mcpskill.org のガイドから始めましょう →設定
{
"mcpServers": {
"IndiaQuant": {
"command": "python",
"args": ["D:/code/mcp/IndiaQuant/server.py"]
}
}
}