MCP for Stock Market Analysis

MCP for Stock Market Analysis

A production-grade MCP server that provides tools to fetch historical stock data, company information, and technical indicators (SMA, EMA, RSI, MACD, Bollinger Bands) via yfinance, and includes a Flask web dashboard for visual analysis.

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README

📈 MCP for Stock Market Analysis

A production-grade Model Context Protocol (MCP) server for stock market analysis, designed to work with Claude Desktop as the AI client. Includes a local Flask web dashboard for visual analysis.

Architecture

graph TD
    subgraph Client Layer
        CD[Claude Desktop]
        FD[Flask Web Dashboard]
    end

    subgraph MCP Layer
        MS[Python MCP Server]
    end

    subgraph Tools
        FS[fetch_stock]
        GC[get_company]
        ST[statistics]
    end

    CD -- stdio --> MS
    FD -- HTTP API --> MS
    
    MS --> FS
    MS --> GC
    MS --> ST
    
    FS -- yfinance --> API[Yahoo Finance API]
    GC -- yfinance --> API

Dashboard Screenshots

Dashboard View Technical Indicators Claude Desktop Integration Company Snapshot

Features

MCP Tools (used by Claude Desktop)

  • fetch_stock — Fetch OHLCV price history for any stock symbol
  • get_company — Company info: sector, market cap, P/E, 52-week range, etc.
  • statistics — Full technical analysis: SMA, EMA, RSI, MACD, Bollinger Bands, Volatility, Support/Resistance

Web Dashboard

  • 🌗 Premium dark theme with glassmorphism
  • 📊 Interactive price charts (Chart.js)
  • 📈 RSI gauge, MACD display, Bollinger Bands visualization
  • 🔍 Stock search with popular picks
  • ⚡ Real-time data fetching

Quick Start

1. Setup Python Environment

cd "MCP for Stock Market Analysis"
python -m venv venv
venv\Scripts\activate          # Windows
# source venv/bin/activate    # Mac/Linux
pip install -r requirements.txt

2. Run the Flask Dashboard

python flask_app/app.py

Open http://localhost:5000 in your browser.

3. Connect to Claude Desktop

Add the following to your Claude Desktop config file:

Windows: %APPDATA%\Claude\claude_desktop_config.json Mac: ~/Library/Application Support/Claude/claude_desktop_config.json

{
    "mcpServers": {
        "stock-market-analysis": {
            "command": "C:\\path\\to\\your\\project\\venv\\Scripts\\python.exe",
            "args": ["C:\\path\\to\\your\\project\\mcp_server\\server.py"]
        }
    }
}

Important: You must replace C:\path\to\your\project\ with the actual absolute path to where you saved this folder on your computer. Make sure to use double backslashes \\ in the JSON!

Restart Claude Desktop. You should see the stock market tools available.

4. Use with Claude Desktop

Ask Claude things like:

  • "Fetch the stock data for AAPL for the last 3 months"
  • "What are the technical indicators for Tesla?"
  • "Give me a full analysis of NVDA including RSI, MACD, and Bollinger Bands"
  • "Compare the volatility of AAPL vs MSFT"

Claude will automatically use the MCP tools to fetch data and provide analysis.

Project Structure

MCP for Stock Market Analysis/
├── mcp_server/                  # MCP Server (Python)
│   ├── server.py                # Main MCP server entry point
│   ├── tools/
│   │   ├── stock_fetcher.py     # Tool 1: Stock data fetcher
│   │   └── statistics_tool.py   # Tool 2: Technical indicators
│   └── database/
│       └── db.py                # SQLite caching layer
│
├── flask_app/                   # Web Dashboard
│   ├── app.py                   # Flask application
│   ├── templates/
│   │   └── index.html           # Dashboard HTML
│   └── static/
│       ├── css/style.css        # Premium dark theme
│       └── js/app.js            # Dashboard logic
│
├── requirements.txt             # Python dependencies
├── claude_desktop_config.json   # Claude Desktop config snippet
├── .env.example                 # Environment template
├── .gitignore
└── README.md

Technical Indicators

Indicator Description Signal
SMA (10, 20, 50) Simple Moving Average Price above SMA = Bullish
EMA (12, 26) Exponential Moving Average EMA12 > EMA26 = Bullish
RSI (14) Relative Strength Index <30 Oversold, >70 Overbought
MACD (12, 26, 9) Moving Average Convergence Divergence Histogram > 0 = Bullish
Bollinger Bands (20, 2σ) Volatility bands Position in band
Volatility Standard deviation of returns Annual risk level
Support/Resistance Key price levels 20-day high/low

API Endpoints (Flask Dashboard)

Endpoint Method Description
/api/stock/<symbol> GET Fetch OHLCV data
/api/company/<symbol> GET Company information
/api/statistics/<symbol> GET Technical indicators
/api/health GET Health check

Query parameters: period (1d, 5d, 1mo, 3mo, 6mo, 1y, 5y), interval (1d, 1wk, 1mo)

Tech Stack

  • MCP Server: Python, mcp[cli] SDK
  • Data: yfinance, pandas, numpy
  • Dashboard: Flask, Chart.js, vanilla CSS
  • Database: SQLite (auto-created)
  • AI Client: Claude Desktop (free tier)

License

MIT

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