Math Mcp Server

Name: Math Mcp Server
Author: 111-test-111

@111-test-111

Math Mcp Server について

This project implements a math MCP server with the help of fastmcp, aiming to provide tools for LLMs to perform complex mathematical calculations and analyses.

#mathgpt #math-solver #math-assistant

基本情報

カテゴリ

開発者ツール

トランスポート

stdio

公開者

111-test-111

投稿者

111-test-111

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "math-calculator": {
      "command": "uvx",
      "args": [
        "math-mcp"
      ],
      "env": {
        "OUTPUT_PATH": "path/to/plot_output",
        "FONT_PATH": "/path/to/font"
      }
    }
  }
}

ツール

Brief description: Basic arithmetic operations tool for standard mathematical operations. For factorial, use mathematical_functions tool instead Examples: basic_arithmetic(operation='add', numbers=[1, 2, 3, 4, 5]) basic_arithmetic(operation='multiply', numbers=[2.5, 3.7], precision=3) basic_arithmetic(operation='power', numbers=[2, 3]) # Calculate 2^3

Brief description: Mathematical function calculation tool, supporting trigonometric, logarithmic, exponential functions, etc. Examples: mathematical_functions(function='sin', value=1.57, angle_unit='radians') mathematical_functions(function='log', value=100, base=10)

Brief description: Number format conversion tool, supporting base conversion, scientific notation, etc. Examples: number_converter(number='255', from_base=10, to_base=16) number_converter(number='1010', from_base=2, to_base=10)

Brief description: Physical unit conversion tool, supporting length, weight, temperature, etc., unit conversions. Examples: unit_converter(value=100, from_unit='cm', to_unit='m', unit_type='length') unit_converter(value=32, from_unit='fahrenheit', to_unit='celsius', unit_type='temperature')

Brief description: High-precision calculation tool using decimal arithmetic for enhanced accuracy. Provides precise calculations where floating-point errors matter. // Examples: precision_calculator(numbers=[1.123, 2.987], operation='add', precision_digits=15) precision_calculator(numbers=[2], operation='sqrt', precision_digits=20) precision_calculator(numbers=[5], operation='factorial', precision_digits=10)

Brief description: Numerical property analysis tool, analyzes various mathematical properties of numbers. Examples: number_properties(number=17, analysis_type='comprehensive') number_properties(number=100, analysis_type='factor')

Brief description: Matrix and linear algebra calculation tool, supporting basic operations and advanced analysis. Examples: matrix_calculator(operation='multiply', matrix_a=[[1,2],[3,4]], matrix_b=[[5,6],[7,8]]) matrix_calculator(operation='eigenvalues', matrix_a=[[4,2],[1,3]])

Brief description: Comprehensive statistical analysis tool, supporting descriptive statistics, hypothesis testing, and distribution analysis. Examples: statistics_analyzer(data1=[1,2,3,4,5], analysis_type='descriptive') statistics_analyzer(data1=[1,2,3], data2=[4,5,6], analysis_type='comparison')

Brief description: Advanced calculus computation engine, supporting derivatives, integrals, limits, series, and differential equations. Examples: calculus_engine(expression='x**2 + 3*x + 1', operation='derivative', variable='x') calculus_engine(expression='sin(x)', operation='integral', variable='x', limits=[0, 3.14159])

Brief description: Professional optimization suite, supporting function optimization, constraint optimization, root finding, and linear programming. Examples: optimization_suite(objective_function='x**2 + y**2', variables=['x', 'y'], operation='minimize') optimization_suite(equation='x**2 - 4', operation='find_roots')

Brief description: Regression analysis and machine learning modeling tool, supporting various regression algorithms and prediction functions. Examples: regression_modeler(operation='fit', x_data=[[1], [2], [3]], y_data=[2, 4, 6], model_type='linear') regression_modeler(operation='predict', x_data=[[12]], training_x=[[1], [2], [3]], training_y=[2, 4, 6])

Brief description: Mathematical expression evaluation and symbolic computation tool. Examples: expression_evaluator(expression='2*x + 3*y', variables={'x': 5, 'y': 7}) expression_evaluator(expression='x**2 + 2*x + 1', mode='factor')

Brief description: Data visualization and chart creation tool, supporting various statistical chart types. Examples: create_and_save_chart(chart_type='line', x_data=[1,2,3,4], y_data=[1,4,2,3], title='Line Plot') create_and_save_chart(chart_type='histogram', data=[1,2,2,3,3,3,4,4,5], filename='histogram_plot')

Brief description: Mathematical function curve plotting tool, supporting function graph visualization and derivative analysis. Examples: plot_function_curve(function_expression='x**2 + 2*x + 1') plot_function_curve(function_expression='sin(x)', x_range=(-6.28, 6.28), filename='sine_wave')

Brief description: Powerful geometry calculation tool, supporting plane geometry, solid geometry, and analytical geometry calculations. Examples: geometry_calculator(shape_type='circle', operation='properties', dimensions={'radius': 5}) geometry_calculator(shape_type='triangle', operation='area', points=[[0,0], [3,0], [0,4]])

Brief description: Advanced number theory calculation tool, supporting prime testing, factorization, modular arithmetic, etc. Examples: number_theory_calculator(operation='prime_factorization', number=60) number_theory_calculator(operation='prime_test', number=97)

Brief description: Professional digital signal processing tool, supporting FFT, filtering, modulation/demodulation, etc. Examples: signal_processing_calculator(operation='generate_signal', signal_type='sine', frequency=10, sampling_rate=1000, duration=1) signal_processing_calculator(operation='fft', signal=[1,2,3,4,5,6,7,8], sampling_rate=8)

Brief description: Professional financial mathematics calculation tool, supporting compound interest, investment analysis, risk assessment, etc. Examples: financial_calculator(operation='compound_interest', principal=1000, rate=0.05, time=10) financial_calculator(operation='npv', cash_flows=[-1000, 300, 400, 500], rate=0.1)

Brief description: Probability and statistics calculation tool, supporting probability distributions, hypothesis testing, Bayesian analysis, etc. Examples: probability_calculator(operation='probability_mass', distribution='normal', parameters={'mu':0,'sigma':1}, x_value=1.96) probability_calculator(operation='cumulative_distribution', distribution='normal', parameters={'mu':20,'sigma':3}, x_value=25) probability_calculator(operation='random_sampling', distribution='binomial', parameters={'n':10,'p':0.3}, n_samples=100)

Brief description: Powerful complex analysis and complex function tool, supporting complex number form conversion, residue calculation, analytic continuation, complex plane visualization, and other advanced features. Examples: complex_analysis_suite(operation='convert_form', complex_number='3+4i') complex_analysis_suite(operation='function_evaluation', function_expression='z**2 + 1', complex_number='1+i') complex_analysis_suite(operation='residue_calculation', function_expression='1/(z**2 + 1)', singularities=['i', '-i'])

Brief description: Professional graph theory analysis tool, supporting shortest path, maximum flow, connectivity analysis, centrality calculation, community detection, spectral analysis, and other comprehensive graph theory functions. Examples: graph_theory_suite(operation='shortest_path', edge_list=[[1,2], [2,3], [1,3]], source_node=1, target_node=3) graph_theory_suite(operation='centrality_analysis', graph_data={'nodes': [1,2,3], 'edges': [[1,2], [2,3]]}) graph_theory_suite(operation='graph_visualization', adjacency_matrix=[[0,1,1],[1,0,1],[1,1,0]], filename='graph_plot')

Brief description: Deletes files generated in OUTPUT_PATH (or default temporary directory) and performs basic resource cleanup. Call only when the user explicitly indicates deletion of temporary or output files. Examples: cleanup_resources()

概要

What is Math Mcp Server?

Math Mcp Server is a Model Context Protocol (MCP) server that provides a collection of mathematical computation tools and plotting utilities, designed for integration with AI assistants or apps that support the MCP protocol.

How to use Math Mcp Server?

Run the server via uvx math-mcp. For use with Claude Desktop, add the configuration block shown in the README to your Claude Desktop config file, optionally setting OUTPUT_PATH and FONT_PATH environment variables.

Key features of Math Mcp Server

Matrix computation: basic operations, decomposition, eigenvalues, SVD
Statistical analysis: descriptive stats, hypothesis testing, distribution analysis
Calculus: derivatives, integrals, limits, Taylor series
Optimization algorithms: function optimization, linear programming, constrained optimization
Regression analysis: linear, polynomial, and regularized regression
Data visualization: statistical charts and function plotting