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. [](https://deepwiki.com/akalaric/mcp-wolframalpha) --- ## 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 ```bash 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 ```bash pip install -r requirements.txt ``` Install the required dependencies with uv: Ensure [`uv`](https://github.com/astral-sh/uv) is installed. ```bash uv sync ``` ### 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](https://sebastian-petrus.medium.com/vscode-mcp-server-42286eed3ee7). To use with Claude Desktop: ```json { "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: ```bash python main.py --ui ``` #### Docker To build and run the client inside a Docker container: ```bash 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: ```bash python main.py ``` #### Docker To build and run the client inside a Docker container: ```bash 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: ```sh printf "\x61\x6b\x61\x6c\x61\x72\x69\x63\x31\x40\x6f\x75\x74\x6c\x6f\x6f\x6b\x2e\x63\x6f\x6d\x0a" ```