Quantitative Analysis Toolkit via MCP

A Model Context Protocol (MCP) artifact delivering sophisticated mathematical and fiscal computation utilities designed for seamless integration with AI programming copilots such as Cline and Roo Code.

Executive Summary

This MCP Utility unveils a suite of mathematical processing capabilities through a standardized interface accessible to AI agents. This abstraction permits automated tools to tackle complex computations by offloading the direct implementation of underlying mathematical procedures.

Core Capabilities

Mathematical Manipulation

• Symbolic Algebra
• differentiate: Compute formal derivatives for mathematical expressions
• integrate: Determine symbolic antiderivatives or definite integrals
• asymptote_value: Assess limits as variables approach designated bounds
• isolate_variable: Solve algebraic structures for target variables

Algorithmic Numerics

• approximate_integral_riemann: Approximate definite integrals using Riemann partitioning (covering left, right, middle, and trapezoidal summation methods)
• bound_sum_darboux: Determine upper and lower Darboux bounds for integration approximation
• planar_area: Calculate the surface area bounded by a function curve between two abscissa values
• revolution_volume: Compute the volume generated by revolving a function around the x-axis

Transform Operations

• laplace_transform_tool: Execute the Laplace transform on time-domain functions
• fourier_transform_tool: Compute the Fourier transform for signal analysis
• z_transform_tool: Calculate the Z-transform for discrete-time sequences

Fiscal Modeling Tools

• future_value_interest: Calculate returns based on compound interest models with variable periodicity
• discounted_value: Determine the present worth of projected future monetary flows
• net_present_worth: Calculate the NPV metric for a sequence of financial outlays and receipts
• black_scholes_pricing: Determine theoretical option valuations using the Black-Scholes framework
• option_sensitivities: Compute option risk metrics (Delta, Gamma, Vega, Theta, Rho)

Auxiliary Functions

• log_base_any: Calculate logarithms across arbitrary bases
• exponential_function: Evaluate the natural exponential function ($e^x$)

Deployment Instructions

bash

Retrieve source code

git clone https://github.com/yourusername/mcp-calc-tools.git

Navigate into the root directory

cd mcp-calc-tools

Install necessary components

npm install

Alternatively

pnpm install

Operational Guide

Launching the MCP Service Endpoint

bash

Ensure execution rights are set (if necessary)

chmod +x index.js

Start the service

npm start

Or directly execute

node index.js

Agent Integration Protocol

To leverage this Quantitative Analysis Toolkit with programming assistants (Cline/Roo Code):

1. Configure the assistant's tool-calling mechanism to point towards this running MCP service URL.
2. Specify the appropriate endpoint address.
3. The agent will then gain sanctioned access to all provided mathematical utilities.

Illustrative invocation for a derivative calculation:

Determine the first derivative of the expression $x^2 \cdot \sin(x)$

Dependencies

• Runtime Environment: Node.js version 14 or superior
• Required NPM packages:
• genkit (~1.0.5)
• genkitx-mcp (~1.0.5)
• mathjs (~12.0.0)

Project Structure Overview

The repository layout is organized as follows:

• index.js: Contains the primary server logic and all defined tool bindings.
• package.json: Manages project dependencies and defined runtime scripts.

Licensing

[Placeholder for licensing information]

Community Contributions

We welcome external enhancements! Feel encouraged to submit a Pull Request for review.