Documentation
Complete reference for all MCP tools and capabilities
Tool Reference
Performs dual-timeframe (daily + weekly) analysis including price action, EMA/SMA crossovers, RSI, MACD, Bollinger Bands, ADX, Ichimoku Cloud, support/resistance levels, pivot points, candlestick patterns, financial ratios, and a comparative daily vs weekly signal alignment report.
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
| ticker | string | required | Stock symbol (e.g. 'AAPL', 'RELIANCE.NS') or crypto (e.g. 'BTCUSD') |
| period | string | optional | Historical data range: '6mo', '1y', or '2y'. Default '1y' |
| include_news | boolean | optional | Auto-run 4x financial news searches and include in response. Default true |
Returns
Comparative analysis text, daily chart image, weekly chart image, file listing, and financial ratios (valuation, profitability, leverage, scores).
Screen stocks across 81 data fields using 57 filter parameters. Supports US, Indian, and crypto markets. Returns matching results with complete data including RSI, MACD, P/E, ROE, Piotroski score, sector, and more.
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
| country | string | optional | Country filter: 'IN' (India), 'US', or 'Crypto' |
| sector | string | optional | Exact sector name (e.g. 'Technology', 'Energy') |
| filters | JSON object | optional | Filter criteria: min/max RSI, P/E, ROE, volume, price, and 50+ more |
| sort_by | string | optional | Sort field: rsi, price, volume, market_cap, pe, roe, etc. |
| index | string | optional | Index name (e.g. 'nifty_50', 'sp500'). Auto-sets country |
| tickers | string[] | optional | Specific list of ticker symbols to screen |
Returns
Matching stocks with 81 fields each, capped at 200 results. Includes distribution stats when zero matches are found.
Execute Python code against a single ticker's OHLCV data to compute custom indicators. Automatically renders a professional multi-pane chart with Bollinger Bands, RSI, and MACD. Pre-loaded with pandas, numpy, 150+ built-in indicators, and yfinance.
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
| ticker | string | required | Stock symbol (e.g. 'AAPL') or crypto (e.g. 'BTCUSD') |
| code | string (Python) | required | Python code that adds columns to the pre-loaded DataFrame 'df' |
| indicator_name | string | required | Human-readable name (e.g. 'SuperTrend', 'KAMA') |
| period | string | optional | Historical data range: '6mo', '1y', or '2y'. Default '1y' |
| plot_type | string | optional | 'overlay' (on price chart) or 'oscillator' (separate pane). Default 'overlay' |
Returns
Preview of the last 20 indicator values, CSV download URL, and chart image.
Lists 150+ technical indicators available across categories like Momentum, Overlap Studies, Volatility, Volume, and Pattern Recognition. Use before writing custom indicator code to check if the desired indicator already exists.
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
| search | string | optional | Filter indicators by name substring (case-insensitive). E.g. 'VWAP', 'momentum' |
Returns
List of matching indicator names and their categories.
Returns the official constituent ticker list for a stock market index. Supports 30+ Indian indices (from niftyindices.com) and US indices (S&P 500, Nasdaq 100, Dow Jones). Returns exact, up-to-date ticker symbols.
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
| index_name | string | required | Index identifier (e.g. 'nifty_50', 'sp500', 'nasdaq100'). Case-insensitive |
Returns
JSON with ticker list and count, ready for use with screen_stocks.
Searches curated financial websites for news, sentiment, and fundamental information. Scoped to trusted sources per market: SeekingAlpha, Yahoo Finance, Bloomberg for US; Moneycontrol, Economic Times for India; CoinDesk, CoinTelegraph for crypto.
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
| query | string | required | Search query (e.g. 'AAPL earnings outlook', 'Bitcoin halving impact') |
| market | string | optional | 'us', 'india', 'crypto', or 'all'. Default 'all' |
| recency | string | optional | 'day', 'week', or 'month'. Default 'month' |
Returns
Top 10 results with titles, URLs, and snippets from curated financial sources.
Fetch a specific file from a ticker's output folder. Supports PNG charts, TXT analysis reports, and CSV data files. Use fuzzy patterns like 'daily', 'weekly_chart', or 'comparative' instead of exact filenames.
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
| ticker | string | required | Ticker symbol (e.g. 'AAPL') |
| filename | string | required | Exact filename or pattern like 'daily', 'weekly_chart', 'comparative' |
Returns
PNG as inline chart image, TXT as report text, CSV as data preview.
Browse analysis outputs on the server. Call without a ticker to see all analyzed tickers. Call with a ticker to list all available files with sizes. Each analysis produces 7 files: 2 chart PNGs, 3 analysis TXTs, and 2 data CSVs.
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
| ticker | string | optional | Ticker symbol. Omit to list all analyzed tickers |
Returns
Without ticker: summary of all ticker folders. With ticker: detailed file listing with types and sizes.
Execute a live market query against Indian stock data using Groww API and the screener database. Runs Python code in a sandbox with pre-loaded market data including historical OHLCV, screener metrics (81 columns), and real-time quotes.
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
| code | string (Python) | required | Python code that assigns a non-empty DataFrame to 'results' |
| query_name | string | required | Human-readable query name (e.g. 'Upper Circuit 5 Days') |
| days | integer | optional | Days of history to load (1-30). Default 30 |
Returns
Query results as a formatted table with the computed DataFrame.
Load any stock tickers into the screener database. Computes all technical indicators and financial ratios in parallel batches. Supports US, Indian (NSE/BSE), UK, and crypto markets. Uses market-aware staleness to determine when to refresh.
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
| tickers | string[] | optional | List of ticker symbols. Defaults to S&P 500 if omitted |
| bg_task | boolean | optional | Run in background. Default true |
| limit | integer | optional | Limit number of stocks to update (for testing) |
Returns
Confirmation of data loading. Background tasks return immediately.
Search the web for a technical indicator formula or Python implementation. Use when the desired indicator is not already built-in. Prioritizes trusted financial authorities like Investopedia and StockCharts.
Parameters
| Parameter | Type | Required | Description |
|---|---|---|---|
| query | string | required | Search query (e.g. 'SuperTrend indicator Python pandas formula') |
Returns
Top 5 web results with titles, URLs, and text snippets.
Example Queries
Copy and paste these into any MCP-compatible AI client to get started.
Analyze a stock
"Analyze AAPL"
// Or with options:
"Analyze RELIANCE with 2 years of data and include news"Screen for oversold stocks
"Find Indian stocks with RSI below 30, ROE above 15%, and P/E under 20"Run a custom indicator
"Run SuperTrend indicator on INFY with ATR period 10 and multiplier 3"Live market query
"Show me stocks hitting upper circuit for 3 consecutive days"Multi-stock comparison
"Compare AAPL, MSFT, and GOOG — show RSI, MACD, and P/E side by side"Index screening
"Screen Nifty Bank for stocks near 52-week low with strong fundamentals"