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

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

cd mcp-wolframalpha

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

pip install -r requirements.txt

Install the required dependencies with uv: Ensure uv is installed.

uv sync

Configuration

To use with the VSCode MCP Server:

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

To use with Claude Desktop:

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

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:

python main.py --ui

Docker

To build and run the client inside a Docker container:

docker build -t wolframalphaui -f .devops/ui.Dockerfile .

docker run wolframalphaui

UI

Intuitive interface built with Gradio to interact with both Google AI (Gemini) and the Wolfram Alpha MCP server.
Allows users to switch between Wolfram Alpha, Google AI (Gemini), and query history.

Run as CLI Tool

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

python main.py

Docker

To build and run the client inside a Docker container:

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

docker run -it wolframalpha

Contact

Feel free to give feedback. The e-mail address is shown if you execute this in a shell:

printf "\x61\x6b\x61\x6c\x61\x72\x69\x63\x31\x40\x6f\x75\x74\x6c\x6f\x6f\x6b\x2e\x63\x6f\x6d\x0a"

MCP_WolframAlpha