compute_indicators

Calculate technical indicators like RSI, MACD, and BBANDS for financial symbols to support trading strategy analysis and portfolio management.

Instructions

Calculates technical indicators for a symbol.

Args:
    symbol: Ticker symbol.
    indicators: List of indicators (e.g., ['RSI', 'MACD', 'BBANDS']).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`symbol`	Yes
`indicators`	No

Implementation Reference

tools/feature_engineering.py:9-41 (handler)

The primary handler function implementing the compute_indicators tool. Downloads 1 year of historical data for the given symbol using yfinance, computes the specified technical indicators (RSI, MACD, Bollinger Bands) using pandas_ta, handles data structure issues, and returns the last 10 rows of results as JSON string.

def compute_indicators(symbol: str, indicators: List[str] = ["RSI", "MACD"]) -> str:
    """
    Calculates technical indicators for a symbol.
    
    Args:
        symbol: Ticker symbol.
        indicators: List of indicators (e.g., ['RSI', 'MACD', 'BBANDS']).
    """
    df = yf.download(symbol, period="1y", progress=False)
    if df.empty:
        return f"No data for {symbol}"
    
    # Handle MultiIndex
    if isinstance(df.columns, pd.MultiIndex):
        df.columns = df.columns.get_level_values(0)
        
    result = df[['Close']].copy()
    
    for ind in indicators:
        try:
            if ind.upper() == "RSI":
                result['RSI'] = ta.rsi(df['Close'])
            elif ind.upper() == "MACD":
                macd = ta.macd(df['Close'])
                result = pd.concat([result, macd], axis=1)
            elif ind.upper() == "BBANDS":
                bb = ta.bbands(df['Close'])
                result = pd.concat([result, bb], axis=1)
            # Add more as needed
        except Exception as e:
            return f"Error computing {ind}: {str(e)}"
            
    return result.tail(10).to_json(orient="index")

server.py:390-393 (registration)
Registration of the compute_indicators tool (along with related functions) as part of the 'Feature Engineering' category in the MCP server using the register_tools helper function, which applies @mcp.tool() decorator to each.
```
register_tools(
    [compute_indicators, rolling_stats, get_technical_summary],
    "Feature Engineering"
)
```

server.py:355-364 (helper)

The register_tools helper function that dynamically registers imported tools like compute_indicators by applying the MCP @mcp.tool() decorator in a loop with logging.

def register_tools(tools: List[Callable], category: str):
    """Helper to register multiple tools with logging."""
    for tool in tools:
        try:
            mcp.tool()(tool)
            logger.info(f"Registered {category} tool: {tool.__name__}")
        except Exception as e:
            logger.error(f"Failed to register {tool.__name__}: {e}")
            raise

app.py:291-291 (registration)
compute_indicators is included in the 'Technical Analysis' tool category for the Gradio UI toolbox (non-MCP usage).
```
"Technical Analysis": [compute_indicators, rolling_stats, get_technical_summary],
```

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