MCP server for Indian stock market analysis — fundamentals, technicals, DCF, peer comparison
Project description
stock-analyst-mcp
MCP server for Indian stock market analysis — fundamentals, technicals, DCF valuation, peer comparison, and more.
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
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