Zentickr Yahoo Query Mcp Server

Zentickr — Yahoo Finance MCP Server

Zentickr is a stdio-based Model Context Protocol (MCP) server that gives AI assistants access to 23 Yahoo Finance tools through the yahooquery library—covering prices, fundamentals, statements, analyst research, ownership, events, and symbol discovery.

⚠️ Important Disclaimer

This software is provided for educational and informational purposes only. It does not provide financial, investment, legal, or tax advice. Market data may be delayed, incomplete, or inaccurate. You are solely responsible for your investment decisions; the authors are not liable for any losses or damages arising from use of this software.

Quickstart

git clone https://github.com/chintan-diwakar/zentickr-yahoo-query-mcp.git
cd zentickr-yahoo-query-mcp
python -m venv .venv && source .venv/bin/activate
pip install -e .

Run the server over stdio:

zentickr

Or:

python -m zentickr

Client setup

Claude Desktop

Add this to claude_desktop_config.json:

{
  "mcpServers": {
    "zentickr": {
      "command": "/absolute/path/to/zentickr-yahoo-query-mcp/.venv/bin/zentickr"
    }
  }
}

Claude Code

claude mcp add zentickr -- /absolute/path/to/zentickr-yahoo-query-mcp/.venv/bin/zentickr

Cursor

Create or update .cursor/mcp.json:

{
  "mcpServers": {
    "zentickr": {
      "command": "/absolute/path/to/zentickr-yahoo-query-mcp/.venv/bin/zentickr"
    }
  }
}

Real-world use cases

Compare Apple and Microsoft fundamentals

Prompt: “Compare Apple and Microsoft fundamentals.”

The assistant can call get_financial_data(symbols="AAPL,MSFT") and get_valuation_measures(symbols="AAPL,MSFT").

Captured output excerpt:

Financial Data:
{
  "AAPL": {
    "currentPrice": 333.26,
    "targetHighPrice": 400.0,
    "targetLowPrice": 215.0,
    "targetMeanPrice": 315.78604,
    "recommendationKey": "buy",
    "numberOfAnalystOpinions": 43,
    "totalCash": 68507000832,
    "totalDebt": 84710998016,
    "totalRevenue": 451442016256,
    "earningsGrowth": 0.218,
    "revenueGrowth": 0.166
  }
}

Valuation Measures:
[
  {
    "symbol": "AAPL",
    "asOfDate": "2026-05-28 00:00:00",
    "periodType": "TTM",
    "ForwardPeRatio": 35.3357,
    "MarketCap": 4589945623560.0,
    "PbRatio": 43.101723,
    "PeRatio": 37.83414,
    "PegRatio": 2.7194
  }
]

Prep me for AAPL earnings

Prompt: “Prep me for AAPL earnings.”

The assistant can call get_calendar_events(symbols="AAPL") and get_earnings_trend(symbols="AAPL").

Captured output excerpts:

Calendar Events:
{
  "AAPL": {
    "earnings": {
      "earningsDate": [
        "2026-07-31 01:30:S"
      ],
      "earningsAverage": 1.89396,
      "earningsLow": 1.83,
      "earningsHigh": 1.99,
      "revenueAverage": 108890141050
    }
  }
}

Earnings Trend:
{
  "AAPL": {
    "trend": [
      {
        "period": "0q",
        "endDate": "2026-06-30",
        "growth": 0.20629999,
        "earningsEstimate": {
          "avg": 1.89396,
          "numberOfAnalysts": 31,
          "yearAgoEps": 1.57
        }
      }
    ]
  }
}

Find NVIDIA's ticker and current price

Prompt: “Find NVIDIA's ticker and current price.”

The assistant can call search_symbols(query="nvidia"), then get_price_data(symbols="NVDA").

Captured output excerpts:

Search Results for 'nvidia':
[
  {
    "symbol": "NVDA",
    "name": "NVIDIA Corporation",
    "type": "EQUITY",
    "exchange": "NMS"
  }
]

Price Data:
{
  "NVDA": {
    "preMarketPrice": 202.155,
    "regularMarketPrice": 207.4,
    "regularMarketDayHigh": 211.08,
    "regularMarketDayLow": 205.85,
    "regularMarketVolume": 116253420,
    "regularMarketPreviousClose": 212.5,
    "exchangeName": "NasdaqGS",
    "marketState": "PRE",
    "symbol": "NVDA"
  }
}

Tool catalog

Market Data

Tool	Arguments	Returns
get_price_data	symbols: str	Current price and trading data
get_summary_detail	symbols: str	Day range, volume, dividend, and 52-week range
get_historical_prices	symbols: str, period: str | None = None, start_date: str | None = None, end_date: str | None = None, interval: str = "1d"	Historical OHLCV price data
get_calendar_events	symbols: str	Upcoming earnings dates and dividend events

Financial Statements

Tool	Arguments	Returns
get_financial_data	symbols: str	Key financial data, including targets, margins, cash, debt, and growth
get_balance_sheet	symbols: str, frequency: str = "annual"	Balance sheet data
get_cash_flow	symbols: str, frequency: str = "annual"	Cash flow statement
get_income_statement	symbols: str, frequency: str = "annual"	Income statement
get_valuation_measures	symbols: str	Market cap, P/E, EV, and price/book measures
get_earnings	symbols: str	Earnings data
get_earnings_trend	symbols: str	Earnings trend estimates

Analysis & Research

Tool	Arguments	Returns
get_recommendations	symbols: str	Analyst recommendations
get_recommendation_trend	symbols: str	Strong buy, buy, hold, sell, and strong sell counts
get_technical_insights	symbols: str	Technical analysis insights
get_esg_scores	symbols: str	Environmental, social, and governance scores
get_company_profile	symbols: str	Company sector, industry, description, and address

Ownership & Governance

Tool	Arguments	Returns
get_major_holders	symbols: str	Major holders breakdown
get_institution_ownership	symbols: str	Institutional ownership
get_insider_holders	symbols: str	Insider holders
get_insider_transactions	symbols: str	Insider transactions
get_fund_ownership	symbols: str	Mutual fund and ETF ownership
get_company_officers	symbols: str	Executives, titles, and compensation

Discovery

Tool	Arguments	Returns
search_symbols	query: str	Matching stock symbols by company name or partial ticker

symbols is a comma-separated string, such as "AAPL,GOOGL,MSFT". Statement frequency accepts "annual" or "quarterly".

Development

Install development dependencies:

pip install -e ".[dev]"

Run the offline test suite and linter:

pytest
ruff check .

See CONTRIBUTING.md for the full contribution guide.

Data source

Data is sourced from Yahoo Finance through the unofficial yahooquery library. It is subject to Yahoo's terms and no API key is required.

License

MIT — see LICENSE.

Support

Please open a GitHub Issue.