Indian Stock Analyst MCP

stock-analyst-mcp

MCP server for global stock market analysis — fundamentals, technicals, DCF valuation, peer comparison, multi-asset support, and more. Works for 50+ regions worldwide.

What's New in v0.5.7

Python 3.13+ Requirement

• Requires Python >=3.13: Fixes uvx picking stale Python 3.12 which caused pandas C extension crashes (ModuleNotFoundError: pandas._libs.pandas_parser)
• uvx stock-analyst-mcp now works without --python: uv/uvx auto-selects 3.13+

What's New in v0.5.6

MCP Framework Migration — FastMCP standalone

• Replaced mcp SDK with standalone fastmcp: Eliminates v2.0.0 breaking changes, no more mcp.server.fastmcp import errors
• Cleaner dependency: fastmcp>=3.4.0,<4.0.0 (Prefect-maintained, actively developed)
• Port configuration: Now passed as kwarg to mcp.run(transport=..., port=...)
• Future-proof: No SDK version conflicts, fastmcp handles all MCP protocol versions

What's New in v0.5.5

News Fix — yfinance format change

• Fixed empty headlines: yfinance now nests news fields under content
• Correct mapping: title, publisher, link, pub_date extracted from content.*
• Backward compatible: still handles legacy top-level news format

What's New in v0.5.4

API Fix — FastMCP.run() compatibility

• Fixed TypeError: FastMCP.run() doesn't accept port kwarg
• Port configuration: Set via mcp.settings.port before calling run()

What's New in v0.5.3

Compatibility Fix — mcp>=1.28 support

• Fixed breaking import: Replaced removed MCPServer with FastMCP from mcp.server.fastmcp
• Pinned mcp dependency: mcp>=1.0.0,<3.0.0 to prevent future breakage
• Added requirements.txt for pip-based installs

What's New in v0.5.2

Screener Fix — screen_stocks works across regions

• Fixed yfinance EquityQuery parameter: _size → size in yf.screen() call, restoring screener results for India and other regions

What's New in v0.5.1

Performance Overhaul — 3-19x faster peer analysis

• Parallel peer fundamentals: ThreadPoolExecutor on get_info() calls (3.7x speedup)
• Batch history downloads: Single yf.download() for all peers (19.3x speedup)
• Parallel snippet fetching: News analysis now fetches article snippets concurrently
• New stock_analyst/utils/ module: Reusable concurrency helpers (parallel_map, parallel_map_dict, batch_download_history)
• Zero new dependencies: Uses stdlib concurrent.futures

Example: Analyzing LOW (US) with 10 peers now takes ~2-3s instead of 8-10s.

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 (any region)
get_fundamentals	Financial ratios: profitability, liquidity, leverage, efficiency, valuation
get_technicals	Technical signals: EMA trend, RSI, MACD, Bollinger Bands
get_peer_comparison	Peer fundamental + technical metrics with rankings (region-scoped)
get_dcf_valuation	DCF: WACC, equity value/share, sensitivity range
get_revenue_forecast	Revenue forecast: base/bull/bear scenarios
get_news	News headlines with VADER sentiment + article snippets + analyst recommendations
get_market_mood	Region-specific indices + volatility index + market assessment
screen_stocks	Screen stocks by filters (sector, PE, ROE, market cap, etc.) in any region
get_screener_filters	List available screener filter keys and sort options
search_tickers	Search for tickers by name or symbol across regions (stocks, ETFs, indices, crypto, etc.)
analyze_asset	Analyze any asset class: stocks, ETFs, indices, commodities, crypto, currencies
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

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

# Market mood (no symbol needed)
stock-analyst --analysis market-mood

# Stock screener (India)
stock-analyst --screen --sector Technology --pe-max 30 --roe-min 0.15
stock-analyst --screen --market-cap-min 50000000000 --sort-by pe --limit 20

# Global stocks (any region)
stock-analyst --symbol AAPL --region us
stock-analyst --symbol 0700.HK --region hk
stock-analyst --screen --region gb --sector Technology --pe-max 25

# Market mood (global)
stock-analyst --analysis market-mood --region us
stock-analyst --analysis market-mood --region de

# Ticker search
stock-analyst --search "Apple" --search-type stock --region us
stock-analyst --search "Bitcoin" --search-type cryptocurrency

# Multi-asset analysis
stock-analyst --symbol SPY --analysis asset --asset-type etf
stock-analyst --symbol GC=F --analysis asset --asset-type commodity
stock-analyst --symbol BTC-USD --analysis asset --asset-type crypto

Configuration

All settings configurable via environment variables with SA_ prefix. Defaults work out of the box for Indian markets (NSE). Supports 50+ regions globally.

Variable	Default	Description
SA_DEFAULT_REGION	in	Region code (us, gb, de, jp, in, etc.)
SA_DEFAULT_EXCHANGE	.NS	NSE (.NS) or BSE (.BO) — for India only
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,
    get_news, get_market_mood, screen_stocks,
    search_tickers, analyze_asset,
)

# Indian stocks (default region)
result = analyze("RELIANCE")
ratios = get_fundamentals("TCS")
signals = get_technicals("INFY", period="6mo")

# Global stocks (any region)
us_stock = analyze("AAPL", region="us")
hk_stock = analyze("0700.HK", region="hk")
uk_stock = analyze("HSBA", region="gb")

# News with sentiment
news = get_news("TCS")
# Returns headlines with sentiment_score, sentiment_label, snippet

# Market mood (region-specific)
mood_in = get_market_mood(region="in")  # Includes MMI from tickertape
mood_us = get_market_mood(region="us")  # S&P 500 + VIX
mood_de = get_market_mood(region="de")  # DAX + VDAX

# Stock screener (any region)
results_in = screen_stocks({"sector": "Technology", "pe_max": 30}, region="in")
results_us = screen_stocks({"sector": "Technology", "pe_max": 40}, region="us")

# Ticker search
apple_results = search_tickers("Apple", instrument_type="stock", region="us")
crypto_results = search_tickers("Bitcoin", instrument_type="cryptocurrency")

# Multi-asset analysis
etf = analyze_asset("SPY", asset_type="etf")
commodity = analyze_asset("GC=F", asset_type="commodity")
crypto = analyze_asset("BTC-USD", asset_type="crypto")
currency = analyze_asset("EURUSD=X", asset_type="currency")

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, stock screener via EquityQuery (50+ regions)
• screener.in — peer discovery + stock screener fallback for India (best-effort, graceful degradation)
• tickertape.in — Market Mood Index (MMI) scraping for India
• VADER — headline sentiment analysis (vaderSentiment)
• India-adjusted defaults — risk-free rate 7%, cost of debt 9%, tax 25%

Supported Regions

50+ regions via yfinance: US, UK, Germany, France, Italy, Spain, Netherlands, Belgium, Switzerland, Austria, Sweden, Norway, Denmark, Finland, Poland, Czech Republic, Romania, Portugal, Greece, Hungary, Ireland, Lithuania, Latvia, Estonia, Canada, Mexico, Brazil, Argentina, Chile, Peru, Colombia, Venezuela, Australia, New Zealand, Japan, South Korea, China, Hong Kong, Singapore, Malaysia, Thailand, Philippines, Indonesia, Vietnam, Pakistan, Sri Lanka, UAE, Saudi Arabia, Kuwait, Qatar, Israel, Egypt, Turkey, South Africa, and more.

Regions Quick Reference

Region	Code	Primary Index	VIX
USA	us	S&P 500 (^GSPC)	^VIX
UK	gb	FTSE 100 (^FTSE)	^VIX
Germany	de	DAX (^GDAXI)	^VDAX
France	fr	CAC 40 (^FCHI)	^VDAX
Japan	jp	Nikkei 225 (^N225)	^VIX
Hong Kong	hk	Hang Seng (^HSI)	^VIX
India	in	Nifty 50 (^NSEI)	^INDIAVIX
Australia	au	ASX 200 (^AXJO)	^VIX
Canada	ca	TSX (^GSPTSE)	^VIX
Brazil	br	Bovespa (^BVSP)	^VIX

License

MIT