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avisangle/calculator-server

by Various

A comprehensive Go-based MCP server for mathematical computations with 13+ tools

A

MCP

avisangle/calculator-server

Added 1 June 2026

#calculator #calculator-mcp #mcp #mcp-calculator #mcp-calculator-server #mcp-server #mcp-servers #portfolio-project

Overview

A Go-based MCP server that exposes 13+ mathematical computation tools for use by AI agents. It wraps common math operations into a standardized interface, allowing language models to perform calculations through tool calls.

Best for

Best for
Developers building MCP-based AI agents that need reliable server-side math capabilities

Use cases

  • Offloading arithmetic and algebraic calculations from an LLM to a dedicated server
  • Enabling precise numeric computations in agentic workflows
  • Providing a consistent math API for MCP-compatible clients

How to use

Install

make run

Tools exposed

  • basic_math
  • advanced_math
  • expression_eval
  • statistical_analysis
  • unit_conversion
  • financial_calculations
  • stats_summary
  • percentile
  • batch_conversion
  • npv
  • irr
  • loan_comparison
  • investment_scenarios

Notes

A Go-based MCP server that exposes 13+ mathematical computation tools for use by AI agents. It wraps common math operations into a standardized interface, allowing language models to perform calculations through tool calls.

6 stars on GitHub. Last updated 2025-09-19.

Use cases

  • Offloading arithmetic and algebraic calculations from an LLM to a dedicated server
  • Enabling precise numeric computations in agentic workflows
  • Providing a consistent math API for MCP-compatible clients

Pros

  • Written in Go for performance and low resource usage
  • Offers a broad set of math tools beyond basic arithmetic
  • Simple MCP integration for existing AI agent frameworks

Cons

  • Small community with only 6 GitHub stars, limited support
  • Requires Go runtime and build tooling to deploy
  • No built-in authentication or access controls

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Written in Go for performance and low resource usage
  • Offers a broad set of math tools beyond basic arithmetic
  • Simple MCP integration for existing AI agent frameworks

Cons

  • Small community with only 6 GitHub stars, limited support
  • Requires Go runtime and build tooling to deploy
  • No built-in authentication or access controls
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