Cover image
Try Now
2025-02-26

Wolframalpha的LLM API的MCP服务器,能够返回结构化知识和求解数学

3 years

Works with Finder

2

Github Watches

8

Github Forks

27

Github Stars

WolframAlpha LLM MCP Server

WolframAlpha LLM MCP Logo

A Model Context Protocol (MCP) server that provides access to WolframAlpha's LLM API. https://products.wolframalpha.com/llm-api/documentation

WolframAlpha MCP Server Example 1

WolframAlpha MCP Server Example 2

Features

  • Query WolframAlpha's LLM API with natural language questions
  • Answer complicated mathematical questions
  • Query facts about science, physics, history, geography, and more
  • Get structured responses optimized for LLM consumption
  • Support for simplified answers and detailed responses with sections

Available Tools

  • ask_llm: Ask WolframAlpha a question and get a structured llm-friendly response
  • get_simple_answer: Get a simplified answer
  • validate_key: Validate the WolframAlpha API key

Installation

git clone https://github.com/Garoth/wolframalpha-llm-mcp.git
npm install

Configuration

  1. Get your WolframAlpha API key from developer.wolframalpha.com

  2. Add it to your Cline MCP settings file inside VSCode's settings (ex. ~/.config/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json):

{
  "mcpServers": {
    "wolframalpha": {
      "command": "node",
      "args": ["/path/to/wolframalpha-mcp-server/build/index.js"],
      "env": {
        "WOLFRAM_LLM_APP_ID": "your-api-key-here"
      },
      "disabled": false,
      "autoApprove": [
        "ask_llm",
        "get_simple_answer",
        "validate_key"
      ]
    }
  }
}

Development

Setting Up Tests

The tests use real API calls to ensure accurate responses. To run the tests:

  1. Copy the example environment file:

    cp .env.example .env
    
  2. Edit .env and add your WolframAlpha API key:

    WOLFRAM_LLM_APP_ID=your-api-key-here
    

    Note: The .env file is gitignored to prevent committing sensitive information.

  3. Run the tests:

    npm test
    

Building

npm run build

License

MIT

相关推荐

  • Joshua Armstrong
  • Confidential guide on numerology and astrology, based of GG33 Public information

  • https://suefel.com
  • Latest advice and best practices for custom GPT development.

  • Alexandru Strujac
  • Efficient thumbnail creator for YouTube videos

  • Emmet Halm
  • Converts Figma frames into front-end code for various mobile frameworks.

  • Elijah Ng Shi Yi
  • Advanced software engineer GPT that excels through nailing the basics.

  • lumpenspace
  • Take an adjectivised noun, and create images making it progressively more adjective!

  • Lists Tailwind CSS classes in monospaced font

  • https://maiplestudio.com
  • Find Exhibitors, Speakers and more

  • tomoyoshi hirata
  • Sony α7IIIマニュアルアシスタント

  • Yusuf Emre Yeşilyurt
  • I find academic articles and books for research and literature reviews.

  • Carlos Ferrin
  • Encuentra películas y series en plataformas de streaming.

  • https://zenepic.net
  • Embark on a thrilling diplomatic quest across a galaxy on the brink of war. Navigate complex politics and alien cultures to forge peace and avert catastrophe in this immersive interstellar adventure.

  • apappascs
  • 发现市场上最全面,最新的MCP服务器集合。该存储库充当集中式枢纽,提供了广泛的开源和专有MCP服务器目录,并提供功能,文档链接和贡献者。

  • ShrimpingIt
  • MCP系列GPIO Expander的基于Micropython I2C的操作,源自ADAFRUIT_MCP230XX

  • jae-jae
  • MCP服务器使用剧作《无头浏览器》获取网页内容。

  • ravitemer
  • 一个功能强大的Neovim插件,用于管理MCP(模型上下文协议)服务器

  • patruff
  • Ollama和MCP服务器之间的桥梁,使本地LLMS可以使用模型上下文协议工具

  • pontusab
  • 光标与风浪冲浪社区,查找规则和MCP

  • av
  • 毫不费力地使用一个命令运行LLM后端,API,前端和服务。

  • Mintplex-Labs
  • 带有内置抹布,AI代理,无代理构建器,MCP兼容性等的多合一桌面和Docker AI应用程序。

  • WangRongsheng
  • 🧑‍🚀 llm 资料总结(数据处理、模型训练、模型部署、 o1 模型、mcp 、小语言模型、视觉语言模型)|摘要世界上最好的LLM资源。

  • appcypher
  • 很棒的MCP服务器 - 模型上下文协议服务器的策划列表

    Reviews

    4 (1)
    Avatar
    user_ikioIQ5P
    2025-04-17

    I have been using the WolframAlpha-LLM-MCP by Garoth, and it has been an impressive tool for leveraging WolframAlpha's capabilities within my applications. The integration is seamless, and the documentation on GitHub is thorough, making it easy to get started. Highly recommend for anyone looking to enhance their projects with powerful computational intelligence.