iflow-mcp_agentx-ai_yahoo-finance-server 0.1.1

Let your AI get comprehensive stock market data from Yahoo Finance including quotes, news, financials, and more.

Yahoo Finance MCP Server

📈 A Model Context Protocol (MCP) server that lets your AI interact with Yahoo Finance - get comprehensive stock market data, news, financials, and more.

✨ Features

• 📊 Stock Data - Get comprehensive ticker information including company details, financials, and trading metrics
• 📰 News Feed - Fetch recent news articles related to specific stock symbols
• 🔍 Search - Find stocks, ETFs, and other financial instruments with news results
• 🏆 Top Entities - Get top performing companies, ETFs, and mutual funds by sector
• 📈 Price History - Fetch historical price data with customizable periods and intervals
• ⚡ Options Chain - Get option chain data for stocks including calls and puts
• 💰 Earnings - Access earnings data including upcoming earnings dates
• 🌐 Proxy Support - Works with HTTP/HTTPS/SOCKS proxies
• 🚀 Fast & Async - Non-blocking operations using asyncio
• 🔧 Easy Integration - Standard MCP protocol for AI assistants

🚀 Quick Start

Prerequisites

• Python 3.11 or higher
• pip or uvx package manager
• (Optional) Proxy server for better reliability

Installation

Using uvx (Recommended)

# Install with namespace
uvx yahoo-finance-server

Using pip

pip install yahoo-finance-server

From source

git clone https://github.com/AgentX-ai/AgentX-mcp-servers.git
cd AgentX-mcp-servers/yahoo_finance_server
pip install -e .

Configuration

Proxy Setup (Recommended)

For better reliability and to avoid rate limiting, set up a proxy:

# HTTP/HTTPS proxy
export PROXY_URL="http://proxy.example.com:8080"

# SOCKS proxy with auth
export PROXY_URL="socks5://user:pass@127.0.0.1:1080/"

Running the Server

# Basic run
yahoo-finance-server

# Run with proxy
PROXY_URL="http://127.0.0.1:7890" yahoo-finance-server

🛠️ API Reference

Available Tools

1. get-ticker-info

Get comprehensive stock information including company details, financials, and trading metrics.

{
  "name": "get-ticker-info",
  "arguments": {
    "symbol": "AAPL"
  }
}

2. get-ticker-news

Get recent news articles for a stock symbol.

{
  "name": "get-ticker-news",
  "arguments": {
    "symbol": "AAPL",
    "count": 10
  }
}

3. search

Search for stocks, ETFs, and other financial instruments with related news.

{
  "name": "search",
  "arguments": {
    "query": "Apple Inc",
    "count": 10
  }
}

4. get-top-entities

Get top performing entities in a sector.

{
  "name": "get-top-entities",
  "arguments": {
    "entity_type": "companies", // Options: "etfs", "mutual_funds", "companies", "growth_companies", "performing_companies"
    "sector": "technology", // See supported sectors below
    "count": 10
  }
}

Supported sectors:

• basic-materials
• communication-services
• consumer-cyclical
• consumer-defensive
• energy
• financial-services
• healthcare
• industrials
• real-estate
• technology
• utilities

5. get-price-history

Get historical price data with customizable periods and intervals.

{
  "name": "get-price-history",
  "arguments": {
    "symbol": "AAPL",
    "period": "1y", // Options: 1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max
    "interval": "1d" // Options: 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo
  }
}

6. ticker-option-chain

Get option chain data for stocks.

{
  "name": "ticker-option-chain",
  "arguments": {
    "symbol": "AAPL",
    "option_type": "call", // Options: "call", "put", "both"
    "date": "2024-01-19" // Optional: YYYY-MM-DD format
  }
}

7. ticker-earning

Get earnings data including historical and upcoming earnings.

{
  "name": "ticker-earning",
  "arguments": {
    "symbol": "AAPL",
    "period": "annual", // Options: "annual", "quarterly"
    "date": "2023-12-31" // Optional: YYYY-MM-DD format
  }
}

🧪 Testing

Using MCP Inspector

npx @modelcontextprotocol/inspector yahoo-finance-server

Manual Testing

python -c "
import asyncio
from yahoo_finance_server.helper import get_ticker_info

async def test():
    info = await get_ticker_info('AAPL')
    print(f'✅ Stock: {info[\"longName\"]}')

asyncio.run(test())
"

📋 Requirements

• Python 3.11+
• yfinance==0.2.62
• requests>=2.31.0
• pandas>=2.0.0
• mcp>=1.9.3

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests
5. Submit a pull request

📄 License

MIT License - see LICENSE file for details.

🔗 Links

• Homepage: GitHub Repository
• Issues: Report Issues
• MCP Documentation: Model Context Protocol

---

Made with ❤️ for the finance community