MCP_WolframAlpha

MCP Wolfram Alpha (Server + Client)

Seamlessly integrate Wolfram Alpha into your chat applications.

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

Included is an MCP-Client example utilizing Gemini via LangChain, demonstrating how to connect large language models to the MCP server for real-time interactions with Wolfram Alpha’s knowledge engine.

Features

• Wolfram|Alpha Integration for math, science, and data queries.
• Modular Architecture Easily extendable to support additional APIs and functionalities.
• Multi-Client Support Seamlessly handle interactions from multiple clients or interfaces.
• MCP-Client example using Gemini (via LangChain).
• UI Support using Gradio for a user-friendly web interface to interact with Google AI and Wolfram Alpha MCP server.

Installation

Clone the Repo

Set Up 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 Client method below.)

Install Requirements

Configuration

To use with the VSCode MCP Server:

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

To use with Claude Desktop:

Client Usage Example

This project includes an LLM client that communicates with the MCP server.

Run with Gradio UI

• Required: GeminiAPI
• Provides a local web interface to interact with Google AI and Wolfram Alpha.
• To run the client directly from the command line:

Docker

To build and run the client inside a Docker container:

UI

Run as CLI Tool

• Required: GeminiAPI
• To run the client directly from the command line:

Docker

To build and run the client inside a Docker container: