stock-analyst-mcp

MCP server for Indian stock market analysis — fundamentals, technicals, DCF valuation, peer comparison, and more.

<!-- mcp-name: io.github.parth-mehta-989/stock-analyst-mcp -->

Install

pip install stock-analyst-mcp

Or run directly without installing:

uvx stock-analyst-mcp

MCP Configuration

Add to your MCP client config (Claude Desktop, Devin, Cursor, etc.):

{
  "mcpServers": {
    "stock-analyst": {
      "command": "uvx",
      "args": ["stock-analyst-mcp"]
    }
  }
}

Or if installed via pip:

{
  "mcpServers": {
    "stock-analyst": {
      "command": "stock-analyst-mcp"
    }
  }
}

Tools

Tool	Description
analyze_stock	Full analysis: fundamentals + technicals + peers + DCF + forecast + news
get_fundamentals	Financial ratios: profitability, liquidity, leverage, efficiency, valuation
get_technicals	Technical signals: EMA trend, RSI, MACD, Bollinger position
get_peer_comparison	Peer fundamental + technical metrics with rankings
get_dcf_valuation	DCF: WACC (India-adjusted), equity value/share, sensitivity range
get_revenue_forecast	Revenue forecast: base/bull/bear scenarios
get_news	Recent headlines + analyst recommendation summary
compare_stocks	Side-by-side comparison of multiple stocks
get_raw_data	Fetch cached raw financials for deep dives
get_config	View current configuration settings for all analysis tools
set_config	Update configuration settings dynamically (e.g., technical analysis period)

Configuration Tools

get_config

Retrieve all current configuration settings. Useful for understanding what parameters are available before calling set_config.

from stock_analyst import get_config

config = get_config()
# Returns dict with sections:
# - data_provider, default_exchange, default_period, cache settings
# - technical_analysis: EMA periods, RSI period, MACD params, Bollinger settings
# - financial_analysis: DCF params, WACC settings, forecast scenarios
# - peer_comparison: max count, metrics to compare
# - output: format, pretty-print settings

set_config

Update configuration dynamically without restarting. Changes affect subsequent tool calls.

from stock_analyst import set_config

# Change technical analysis period from 1y to 1d
result = set_config("default_period", "1d")
# Returns: {"status": "success", "key": "default_period", "new_value": "1d", "affected_tools": ["all_tools"]}

# Change RSI period from 14 to 21
result = set_config("ta_rsi_period", "21")
# Returns: {"status": "success", "key": "ta_rsi_period", "new_value": 21, "affected_tools": ["get_technicals", "analyze_stock"]}

# Change DCF projection years from 5 to 10
result = set_config("fa_dcf_projection_years", "10")
# Returns: {"status": "success", "key": "fa_dcf_projection_years", "new_value": 10, "affected_tools": ["get_dcf_valuation", "get_revenue_forecast", "analyze_stock"]}

Common Configuration Keys:

Key	Type	Default	Description	Affects
default_period	str	1y	Historical period: 1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, max	all_tools
ta_rsi_period	int	14	RSI calculation period	get_technicals, analyze_stock
ta_ema_periods	str	20,50,200	Comma-separated EMA periods	get_technicals, analyze_stock
ta_macd_params	str	12,26,9	MACD (fast, slow, signal)	get_technicals, analyze_stock
ta_bollinger_enabled	bool	true	Enable Bollinger Bands	get_technicals, analyze_stock
ta_bollinger_period	int	20	Bollinger Bands period	get_technicals, analyze_stock
fa_dcf_enabled	bool	true	Run DCF valuation	analyze_stock, get_dcf_valuation
fa_dcf_projection_years	int	5	DCF projection years	get_dcf_valuation, get_revenue_forecast, analyze_stock
fa_dcf_terminal_growth	float	0.025	Terminal growth rate (2.5%)	get_dcf_valuation, analyze_stock
fa_dcf_exit_multiple	float	12.0	Exit multiple for DCF	get_dcf_valuation, analyze_stock
fa_wacc_risk_free_rate	float	0.07	Risk-free rate (7% for India)	get_dcf_valuation, analyze_stock
fa_wacc_equity_risk_premium	float	0.06	Equity risk premium (6%)	get_dcf_valuation, analyze_stock
fa_wacc_cost_of_debt	float	0.09	Cost of debt (9% for India)	get_dcf_valuation, analyze_stock
fa_wacc_tax_rate	float	0.25	Tax rate (25% for India)	get_dcf_valuation, analyze_stock
peers_max_count	int	10	Max peers to compare	get_peer_comparison, analyze_stock
cache_ttl	int	3600	Cache TTL in seconds	all_tools

Example: Customize Technical Analysis

from stock_analyst import set_config, get_technicals

# Use 1-day data with custom RSI period
set_config("default_period", "1d")
set_config("ta_rsi_period", "21")

# Get technicals with new settings
signals = get_technicals("RELIANCE")

Example: Customize DCF Valuation

from stock_analyst import set_config, get_dcf_valuation

# Use 10-year projection with different growth assumptions
set_config("fa_dcf_projection_years", "10")
set_config("fa_dcf_terminal_growth", "0.03")  # 3% terminal growth
set_config("fa_wacc_risk_free_rate", "0.065")  # 6.5% risk-free rate

# Get DCF with new assumptions
valuation = get_dcf_valuation("RELIANCE")

CLI

Also works as a standalone CLI (no LLM needed):

# Full analysis
stock-analyst --symbol RELIANCE

# Specific analysis
stock-analyst --symbol TCS --analysis fundamentals
stock-analyst --symbol INFY --analysis technicals
stock-analyst --symbol RELIANCE --analysis dcf

# Compare multiple stocks
stock-analyst --symbols RELIANCE,TCS,INFY --compare

# Markdown output
stock-analyst --symbol RELIANCE --format markdown

# Raw data
stock-analyst --symbol RELIANCE --raw financials

Configuration

All settings configurable via environment variables with SA_ prefix. Defaults work out of the box for Indian markets (NSE).

Variable	Default	Description
SA_DEFAULT_EXCHANGE	.NS	NSE (.NS) or BSE (.BO)
SA_DEFAULT_PERIOD	1y	Historical data period
SA_CACHE_BACKEND	redis	redis, csv, or none
SA_REDIS_URL	redis://localhost:6379/0	Redis connection URL
SA_CACHE_TTL	3600	Cache TTL in seconds
SA_SCREENER_ENABLED	true	Use screener.in as fallback for peers
SA_FA_DCF_ENABLED	true	Run DCF valuation
SA_FA_WACC_RISK_FREE_RATE	0.07	India 10Y govt bond yield
SA_PEERS_MAX_COUNT	10	Max peers to compare
SA_MCP_TRANSPORT	stdio	stdio or streamable-http
SA_MCP_PORT	3001	Port for streamable-http

See configurations.env.example for the full list.

Python Library

from stock_analyst import analyze, get_fundamentals, get_technicals

result = analyze("RELIANCE")
ratios = get_fundamentals("TCS")
signals = get_technicals("INFY", period="6mo")

Testing

# Install dev dependencies
pip install -e ".[dev]"

# Run all tests
pytest

# Run with coverage
pytest --cov=stock_analyst --cov-report=term-missing

# Run specific test file
pytest tests/test_peers.py -v

Data Sources

• yfinance — OHLCV, financials, balance sheet, cashflow, info, peer discovery via Industry API
• screener.in — peer discovery fallback (best-effort, graceful degradation)
• India-adjusted defaults — risk-free rate 7%, cost of debt 9%, tax 25%

License

MIT