README.md•3.44 kB
# 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"
```