productivitydeveloper-tools

Calculator

githejie

by githejie

Use Calculator for quick, secure payroll and percentage calculations. Try our percentage calculator and payroll calculat

Provides a secure mathematical expression evaluation service using Python's AST module for basic operations without relying on eval(), enabling quick calculations within conversations.

github stars

146

0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

Secure AST-based evaluationNo API key neededZero setup with uv

best for

  • / AI assistants needing reliable math calculations
  • / Developers building chatbots with numerical capabilities
  • / Applications requiring secure expression evaluation

capabilities

  • / Calculate mathematical expressions
  • / Perform basic arithmetic operations
  • / Evaluate complex numerical formulas
  • / Process mathematical computations securely

what it does

Evaluates mathematical expressions securely using Python's AST module instead of eval(). Enables precise numerical calculations in AI conversations.

about

Calculator is a community-built MCP server published by githejie that provides AI assistants with tools and capabilities via the Model Context Protocol. Use Calculator for quick, secure payroll and percentage calculations. Try our percentage calculator and payroll calculat It is categorized under productivity, developer tools. This server exposes 1 tool that AI clients can invoke during conversations and coding sessions.

how to install

You can install Calculator in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport. This server supports remote connections over HTTP, so no local installation is required.

license

MIT

Calculator is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

Calculator MCP Server

A Model Context Protocol server for calculating. This server enables LLMs to use calculator for precise numerical calculations.

Available Tools

  • calculate - Calculates/evaluates the given expression.
    • expression (string, required): Expression to be calculated

Installation

Using uv (recommended)

When using uv no specific installation is needed. We will use uvx to directly run mcp-server-calculator.

curl -LsSf https://astral.sh/uv/install.sh | sh

Using PIP

Alternatively you can install mcp-server-calculator via pip:

pip install mcp-server-calculator

After installation, you can run it as a script using:

python -m mcp_server_calculator

Configuration

Using uv (recommended)

Add this to your MCP client settings:

"mcpServers": {
  "calculator": {
    "command": "uvx",
    "args": ["mcp-server-calculator"]
  }
}

Using PIP

Alternatively add this to your MCP client settings:

"mcpServers": {
  "calculator": {
    "command": "python",
    "args": ["-m", "mcp_server_calculator"]
  }
}

License

mcp-server-calculator is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

FAQ

What is the Calculator MCP server?
Calculator is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Calculator?
This profile displays 69 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

Use Cases

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

Complete complex tasks end-to-end without manual steps

Implementation Guide

Prerequisites

  • Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • Basic understanding of MCP architecture and capabilities
  • Access credentials for integrated services (if required)
  • Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • MCP server not loading: Check config syntax, verify installation
  • Connection errors: Check network, firewall, credentials
  • Feature not working: Read server docs, check required parameters
  • Performance issues: Monitor resource usage, check for network latency
  • Conflicts with other servers: Check port assignments, namespace collisions

Best Practices

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • Don't grant overly permissive access to MCP servers
  • Don't skip reading security considerations in docs
  • Don't expose sensitive data without proper controls
  • Don't run untrusted MCP servers without code review
  • Don't ignore error messages—investigate root cause

💡 Pro Tips

  • Combine multiple MCP servers for powerful workflows
  • Create custom MCP servers for your specific needs
  • Share successful configurations with team
  • Use MCP inspector for debugging
  • Join MCP community for tips and troubleshooting

Technical Details

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration

  • Tool composition: Chain multiple MCP tools in workflows
  • Context augmentation: Provide AI with relevant external data
  • Action delegation: Let AI execute tasks on external systems
  • Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.669 reviews
  • Liam Huang· Dec 28, 2024

    I recommend Calculator for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • Diego Verma· Dec 24, 2024

    Strong directory entry: Calculator surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • Aarav Abebe· Dec 20, 2024

    Calculator is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Chinedu Wang· Dec 12, 2024

    Calculator reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Harper Rahman· Nov 19, 2024

    According to our notes, Calculator benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • Ama Bhatia· Nov 15, 2024

    Calculator has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • Layla Ghosh· Nov 11, 2024

    Calculator reduced integration guesswork — categories and install configs on the listing matched the upstream repo.

  • Liam Park· Nov 7, 2024

    Calculator is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • Ama Okafor· Nov 3, 2024

    Calculator is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.

  • Ishan Abbas· Oct 26, 2024

    We wired Calculator into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

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