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Math

Provides MCP tools for calculations, unit conversion, statistics, number formatting, and percentage operations.

Install Math

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Open setup steps on GitHub

Overview

Safe expression evaluation is the core of this math MCP server, which also handles unit conversion, statistics, formatting, and percentage calculations. It runs as a Node.js MCP process and exposes five tools for AI agents, without requiring external services or environment variables. Reach for it when an agent needs repeatable numerical operations instead of interpreting arithmetic or conversion rules in text.

Use cases

  • Evaluate formulas with variables and supported functions
  • Convert measurements across supported unit categories
  • Summarize datasets and calculate correlations
  • Format values for reports and technical output
  • Calculate tips, discounts, markups, and percentage changes

Key features

  • Safe expression evaluation without eval
  • Conversion across six unit categories
  • Dataset statistics and correlation
  • Multiple numeric output formats
  • Common percentage calculations

Tools5

What Math lets your agent do. Expand a tool for its parameters.

Self-reported~215 tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 2d ago

Recent health check succeeded.

4/4 checks healthy over the last 39d

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

Last commit7mo agoMost recent push to the default branch.
Tools exposed5Callable tools this server registers over MCP.
Directory activity1 viewsConfig copies, upvotes, and views on AllMCPs.

How Math works

What math MCP server does

The math MCP server gives AI agents a set of focused numerical tools through the Model Context Protocol. It covers expression evaluation, unit conversion, descriptive statistics, number formatting, and common percentage operations. The tools are useful for calculations that need explicit operators, supported functions, consistent output formats, or named input values.

The server does not connect to a remote database, SaaS API, or data warehouse. Its documented inputs are expressions, numbers, units, arrays, and formatting options supplied through MCP tool calls. That makes the math MCP server a fit for local agent workflows where calculations should be delegated to a defined tool rather than generated as prose.

How it works

Install the project with npm, build it, and run the generated Node.js entry point as an MCP server. An MCP-compatible client starts the process and sends tool requests over the configured connection. The README provides a Claude Desktop configuration that invokes node with dist/index.js.

Expression evaluation is described as safe and does not use JavaScript eval. The calculator accepts arithmetic operators, parentheses, named variables, constants such as pi and e, and functions including square root, rounding, logarithms, trigonometry, minimum, maximum, and powers.

Setup and configuration

The documented setup requires Node.js project commands:

Terminal
npm install
npm run build

After building, configure the MCP client to launch the compiled file. A Claude Desktop entry uses a server name such as math-tools, the node command, and an argument pointing to path/to/mcp-math-tools/dist/index.js. Replace that path with the location of the built project on the host machine.

No environment variables are documented as required. The provided setup is local and does not specify credentials, network endpoints, or service configuration.

Tools and capabilities

The math MCP server exposes five tools:

  • calculate evaluates arithmetic and supported mathematical functions. It also accepts variables and constants.
  • convert_units converts length, weight, temperature, data, time, and speed values. Examples include kilometers per hour to miles per hour and conversions between bytes, kilobytes, megabytes, gigabytes, and terabytes.
  • statistics analyzes datasets with mean, median, mode, variance, standard deviation, minimum, maximum, range, percentile, correlation between two arrays, and a full summary mode.
  • format_number renders values as currency, percentages, scientific notation, binary, octal, hexadecimal, significant figures, or numbers with thousands separators.
  • percentage_calc handles percentage-of calculations, percentage comparisons, percentage change, tips, discounts, and markups.

Limitations and notes

Unit conversion is limited to the six documented categories and their listed units. The calculator supports the functions and operators specified by the project rather than arbitrary JavaScript execution. Statistical operations require datasets, while correlation requires two arrays. Formatting and percentage results depend on the options supplied to their respective tools.

The README demonstrates use with Claude Desktop but does not document authentication, hosted deployment, persistent storage, or client-specific behavior beyond launching the local process.

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Frequently Asked Questions about Math

math is an MCP server that connects AI agents to local numerical tools for calculation and analysis. Its main tools are calculate, convert_units, statistics, format_number, and percentage_calc, covering expressions, unit conversion, datasets, number formatting, tips, discounts, markups, and other percentage operations.

Install it with npm install, then build it with npm run build. Configure an MCP client to run node against the compiled dist/index.js file.

Yes, math works with Claude Desktop through a local Node.js process. Add an mcpServers entry that uses the node command and points its args to the built dist/index.js file, replacing the example path with the project’s actual location.

It converts units in six categories: length, weight, temperature, data, time, and speed. Supported examples include meters, miles, kilograms, pounds, Celsius, Fahrenheit, bytes, gigabytes, seconds, hours, kilometers per hour, miles per hour, and knots.

Yes, its statistics tool calculates mean, median, mode, variance, standard deviation, minimum, maximum, range, percentiles, and correlations between two arrays. It also provides a full summary mode for a dataset.

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