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SAGAAIDEV

MCP Ahrefs

by SAGAAIDEV
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Python
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Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Capabilities

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription
echo_tool

Echo back the input message.

This is a simple example tool that demonstrates basic MCP tool functionality.
It will be automatically decorated with SAAGA decorators for exception handling
and logging.

Args:
    message: The message to echo back
    
Returns:
    The echoed message with a prefix
get_time

Get the current time.

Returns the current time in a human-readable format.

Returns:
    Current time as a string
random_number

Generate a random number within a specified range.

Args:
    min_value: Minimum value (default: 1)
    max_value: Maximum value (default: 100)
    
Returns:
    Dictionary containing the random number and range info
calculate_fibonacci

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
process_batch_data

Parallelized version of process_batch_data.

This function accepts a list of keyword argument dictionaries and executes process_batch_data concurrently for each set of arguments.

Original function signature: process_batch_data(items: List, operation: str)

Args: kwargs_list (List[Dict[str, Any]]): A list of dictionaries, where each dictionary provides the keyword arguments for a single call to process_batch_data.

Returns: List[Any]: A list containing the results of each call to process_batch_data, in the same order as the input kwargs_list.

Original docstring: Process a batch of data items.

This is an example of a tool that benefits from parallelization.
It will be automatically decorated with the parallelize decorator
in addition to exception handling and logging.

Args:
    items: List of strings to process
    operation: Operation to perform ('upper', 'lower', 'reverse')
    
Returns:
    Processed items with metadata
simulate_heavy_computation

Parallelized version of simulate_heavy_computation.

This function accepts a list of keyword argument dictionaries and executes simulate_heavy_computation concurrently for each set of arguments.

Original function signature: simulate_heavy_computation(complexity: int)

Args: kwargs_list (List[Dict[str, Any]]): A list of dictionaries, where each dictionary provides the keyword arguments for a single call to simulate_heavy_computation.

Returns: List[Any]: A list containing the results of each call to simulate_heavy_computation, in the same order as the input kwargs_list.

Original docstring: Simulate a heavy computation task.

This tool demonstrates parallelization benefits by performing
a computationally intensive task that can be parallelized.

Args:
    complexity: Complexity level (1-10, higher = more computation)
    
Returns:
    Dictionary containing computation results

Prompts

Interactive templates invoked by user choice

NameDescription

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Resources

Contextual data attached and managed by the client

NameDescription

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