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Yahoo Finance MCP Server

by citizenhicks
GitHub
Python
1
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Yahoo Finance MCP Server

A Model Context Protocol (MCP) server that provides Yahoo Finance data through FastMCP v2 with HTTP streaming support. This server enables AI assistants to access real-time financial data, historical prices, company information, and market analysis tools. The server is primarily built for ThinkingSand AI agents, but can be deployed locally as well.

Features

  • Real-time Stock Data: Current prices, historical data, and company information

  • Financial Statements: Income statements, balance sheets, and cash flow data

  • Options Trading: Option chains, expiration dates, and pricing data

  • Market News: Latest financial news and analysis

  • Institutional Data: Holder information and insider transactions

  • Analyst Coverage: Recommendations and upgrades/downgrades

  • HTTP Streaming: Fast, efficient data delivery with FastMCP v2

Available Tools

Tool

Description

Parameters

get_historical_stock_prices

Historical stock price data

ticker

,

period

,

interval

get_stock_info

Comprehensive company and stock information

ticker

get_yahoo_finance_news

Latest news articles for a stock

ticker

get_stock_actions

Dividend and stock split history

ticker

get_financial_statement

Financial statements (income, balance, cashflow)

ticker

,

financial_type

get_holder_info

Institutional and insider holder data

ticker

,

holder_type

get_option_expiration_dates

Available options expiration dates

ticker

get_option_chain

Option chain data for calls and puts

ticker

,

expiration_date

,

option_type

get_recommendations

Analyst recommendations and upgrades

ticker

,

recommendation_type

,

months_back

Installation & Setup

Prerequisites

  • Python 3.11 or higher

  • uv package manager

Using uv (Recommended)

# Clone the repository git clone https://github.com/citizenhicks/yahoo-finance-mcp.git cd yahoo-finance-mcp # Install dependencies uv sync # Run the server uv run python server.py

Configuration

Environment Variables

Create a .env file (copy from .env.example):

# Server configuration HOST=127.0.0.1 # Server host PORT=8000 # Server port LOG_LEVEL=INFO # Logging level

Starting the Server

uv run python server.py

The server will start on http://127.0.0.1:8000 by default and display:

Starting Yahoo Finance MCP Server locally on 127.0.0.1:8000...

Tool Documentation

1. Historical Stock Prices

get_historical_stock_prices(ticker="AAPL", period="1mo", interval="1d")

  • ticker: Stock symbol (e.g., "AAPL", "TSLA", "GOOGL")

  • period: 1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max

  • interval: 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo

2. Stock Information

get_stock_info(ticker="AAPL")

Returns comprehensive company data including current price, market cap, financial metrics, and company details.

3. Financial Statements

get_financial_statement(ticker="AAPL", financial_type="income_stmt")

  • financial_type: income_stmt, quarterly_income_stmt, balance_sheet, quarterly_balance_sheet, cashflow, quarterly_cashflow

4. Holder Information

get_holder_info(ticker="AAPL", holder_type="institutional_holders")

  • holder_type: major_holders, institutional_holders, mutualfund_holders, insider_transactions, insider_purchases, insider_roster_holders

5. Options Data

# Get available expiration dates get_option_expiration_dates(ticker="AAPL") # Get option chain get_option_chain(ticker="AAPL", expiration_date="2024-01-19", option_type="calls")

  • option_type: calls or puts

6. Recommendations

get_recommendations(ticker="AAPL", recommendation_type="recommendations", months_back=12)

  • recommendation_type: recommendations, upgrades_downgrades

  • months_back: Number of months for historical upgrades/downgrades

MCP Client Integration

Claude Desktop

Add to your Claude Desktop MCP settings (~/.claude/claude_desktop_config.json):

{ "mcpServers": { "yahoo-finance": { "command": "uv", "args": ["run", "python", "/path/to/yahoo-finance-mcp/server.py"], "env": { "HOST": "127.0.0.1", "PORT": "8000" } } } }

HTTP Client Integration

Connect directly to the HTTP endpoint:

http://127.0.0.1:8000

Python Client Example

import asyncio from fastmcp import Client async def example(): client = Client("http://127.0.0.1:8000") async with client: # Get Apple stock info result = await client.call_tool("get_stock_info", {"ticker": "AAPL"}) print(result) # Get historical prices result = await client.call_tool("get_historical_stock_prices", { "ticker": "AAPL", "period": "1y", "interval": "1d" }) print(result) asyncio.run(example())

Project Structure

yahoo-finance-mcp/ ├── server.py # Main FastMCP server implementation ├── main.py # Alternative entry point ├── pyproject.toml # Project dependencies and metadata ├── .env.example # Environment configuration template ├── .env # Your local environment variables (gitignored) └── README.md # This documentation

Error Handling

The server includes robust error handling:

  • Invalid tickers: Returns clear error messages for non-existent symbols

  • Missing data: Graceful handling when specific data isn't available

  • Network issues: Proper error reporting for Yahoo Finance API issues

  • Parameter validation: Clear error messages for invalid parameters

Example error response:

"Error: Company ticker INVALID123 not found"

Data Sources

All financial data is sourced from Yahoo Finance through the yfinance Python library:

  • Stock prices: Real-time and historical market data

  • Company information: Fundamentals, metrics, and company details

  • Financial statements: Official SEC filings and quarterly reports

  • Options data: Real-time options chains and pricing

  • News: Latest financial news and analyst coverage

  • Institutional data: Holdings and insider transaction data

Production Deployment

Docker (Optional)

FROM python:3.11-slim WORKDIR /app COPY . . RUN pip install uv RUN uv sync EXPOSE 8000 CMD ["uv", "run", "python", "server.py"]

Environment Variables for Production

HOST=0.0.0.0 PORT=8000 LOG_LEVEL=INFO

Contributing

  1. Fork the repository

  2. Create a feature branch

  3. Add new tools or improve existing ones

  4. Update tests and documentation

  5. Submit a pull request

License

This project is open source. Yahoo Finance data is subject to Yahoo's terms of service.

Troubleshooting

Common Issues

  1. Server won't start: Check if port 8000 is available

  2. Tool failures: Verify internet connection for Yahoo Finance API

  3. Import errors: Ensure all dependencies are installed with uv sync

Debug Mode

Set LOG_LEVEL=DEBUG in your .env file for detailed logging.

Support

Built with FastMCP v2 and yfinance

This server cannot be installed

-
security - not tested
F
license - not found
-
quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

Enables AI assistants to access real-time financial data, historical stock prices, company information, financial statements, options data, market news, and analyst recommendations through Yahoo Finance. Built with FastMCP v2 for efficient HTTP streaming and comprehensive market analysis tools.

  1. Features
    1. Available Tools
      1. Installation & Setup
        1. Prerequisites
        2. Using uv (Recommended)
      2. Configuration
        1. Environment Variables
        2. Starting the Server
      3. Tool Documentation
        1. 1. Historical Stock Prices
        2. 2. Stock Information
        3. 3. Financial Statements
        4. 4. Holder Information
        5. 5. Options Data
        6. 6. Recommendations
      4. MCP Client Integration
        1. Claude Desktop
        2. HTTP Client Integration
        3. Python Client Example
      5. Project Structure
        1. Error Handling
          1. Data Sources
            1. Production Deployment
              1. Docker (Optional)
              2. Environment Variables for Production
            2. Contributing
              1. License
                1. Troubleshooting
                  1. Common Issues
                  2. Debug Mode
                2. Support

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