MCP Wolframalpha

🚀 MCP Wolfram Alpha (Client + Server)

Seamlessly integrate Wolfram Alpha into your chat applications.

This project implements an MCP (Model Context Protocol) server designed specifically to interface with the Wolfram Alpha API. It enables chat-based applications to execute computational queries and retrieve structured knowledge, thereby enabling advanced conversational capabilities.

It includes an example of an MCP client using Gemini (via LangChain), demonstrating how to connect a large language model to the MCP server for real-time interaction with the Wolfram Alpha knowledge engine.

🚀 Quick Start

This project enables seamless integration of Wolfram Alpha into chat applications. It consists of an MCP server interfacing with the Wolfram Alpha API and provides an example MCP client using Gemini via LangChain.

✨ Features

• Wolfram|Alpha Integration: For mathematical, scientific, and data queries.
• Modular Architecture: Easy to extend to support other APIs and features.
• Multi-Client Support: Seamlessly handle interactions from multiple clients or interfaces.
• MCP Client Example: Using Gemini (via LangChain).

📦 Installation

Clone the Repository

git clone https://github.com/ricocf/mcp-wolframalpha.git

cd mcp-wolframalpha

Set Environment Variables

Create a .env file based on the example:

• WOLFRAM_API_KEY=your_wolframalpha_appid
• GeminiAPI=your_google_gemini_api_key (Optional, if using the following client method)

Install Dependencies

pip install -r requirements.txt

Configuration

Use with VSCode MCP Server

1. Create a .mcp.json file in the project root directory.
2. Use the example in configs/vscode_mcp.json as a template.
3. For more details, refer to VSCode MCP Server Guide.

Use with Claude Desktop

{
  "mcpServers": {
    "WolframAlphaServer": {
      "command": "python3",
      "args": [
        "/path/to/src/core/server.py"
      ]
    }
  }
}

💻 Usage Examples

Basic Usage

Run as a CLI Tool

• Requirement: GeminiAPI
• Run the client directly from the command line:

python main.py

Advanced Usage

Docker

Build and run the client in a Docker container:

docker build -t wolframalpha -f .devops/llm.Dockerfile .

docker run -it wolframalpha