Wolfram Alpha

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.

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Wolfram|Alpha Integrationfor math, science, and data queries.

Modular ArchitectureEasily extendable to support additional APIs and functionalities.

Multi-Client SupportSeamlessly handle interactions from multiple clients or interfaces.

MCP-Client exampleusing Gemini (via LangChain).

UI Supportusing Gradio for a user-friendly web interface to interact with Google AI and Wolfram Alpha MCP server.

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

Create a .env file based on the example:

GeminiAPI=your_google_gemini_api_key(Optional if using Client method below.)

Install the required dependencies with uv: Ensureuvis installed.
- Create a configuration file at.vscode/mcp.jsonin your project root.
- Use the example provided inconfigs/vscode_mcp.jsonas a template.
- For more details, refer to theVSCode MCP Server Guide.

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

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

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

To build and run the client inside a Docker container:

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

- 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.

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

To build and run the client inside a Docker container:

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

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"

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