calculate_fibonacci

Compute Fibonacci sequence values for SEO analysis and data processing tasks. Enter position n to generate the corresponding Fibonacci number with calculation details.

Instructions

Calculate the nth Fibonacci number.

This is a more computationally intensive example that demonstrates
how tools can handle more complex operations.

Args:
    n: The position in the Fibonacci sequence (must be >= 0)
    
Returns:
    Dictionary containing the Fibonacci number and calculation info

Input Schema

TableJSON Schema

Name	Required	Description	Default
`n`	Yes

Implementation Reference

mcp_ahrefs/tools/example_tools.py:61-92 (handler)

The main handler function that computes the nth Fibonacci number using an iterative approach, handles input validation, measures computation time, and returns structured results.

async def calculate_fibonacci(n: int) -> Dict[str, Any]:
    """Calculate the nth Fibonacci number.
    
    This is a more computationally intensive example that demonstrates
    how tools can handle more complex operations.
    
    Args:
        n: The position in the Fibonacci sequence (must be >= 0)
        
    Returns:
        Dictionary containing the Fibonacci number and calculation info
    """
    if n < 0:
        raise ValueError("n must be non-negative")
    
    if n <= 1:
        return {"position": n, "value": n, "calculation_time": 0}
    
    start_time = time.time()
    
    # Calculate Fibonacci number
    a, b = 0, 1
    for _ in range(2, n + 1):
        a, b = b, a + b
    
    calculation_time = time.time() - start_time
    
    return {
        "position": n,
        "value": b,
        "calculation_time": calculation_time
    }

mcp_ahrefs/server/app.py:97-112 (registration)

Registers calculate_fibonacci (as part of example_tools) with the MCP server by applying SAAGA decorators and using FastMCP's tool decorator.

# Register regular tools with SAAGA decorators
for tool_func in example_tools:
    # Apply SAAGA decorator chain: exception_handler → tool_logger
    decorated_func = exception_handler(tool_logger(tool_func, config.__dict__))
    
    # Extract metadata from the original function
    tool_name = tool_func.__name__
    
    # Register the decorated function directly with MCP
    # This preserves the function signature for parameter introspection
    mcp_server.tool(
        name=tool_name
    )(decorated_func)
    
    unified_logger.info(f"Registered tool: {tool_name}")

mcp_ahrefs/tools/example_tools.py:178-183 (registration)
Includes calculate_fibonacci in the list of regular example tools that get automatically registered.
```
example_tools = [
    echo_tool,
    get_time,
    random_number,
    calculate_fibonacci
]
```

MCP Ahrefs