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https://github.com/SecretiveShell/MCP-wolfram-alpha

Connect your chat repl to wolfram alpha computational intelligence
https://github.com/SecretiveShell/MCP-wolfram-alpha

mcp mcp-server wolfram wolfram-alpha

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Connect your chat repl to wolfram alpha computational intelligence

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# MCP-wolfram-alpha

A MCP server to connect to wolfram alpha API.



## Components

### Prompts

This is analogous to the `!wa` bang in duckduckgo search.

```python
def wa(query: str) -> f"Use wolfram alpha to answer the following question: {query}"
```

### Tools

Query Wolfram Alpha api.

```python
def query_wolfram_alpha(query: str) -> str
```

## Configuration

You **must** set the `WOLFRAM_API_KEY` environment variable. Get an api ket from [Wolfram Alpha](https://products.wolframalpha.com/api).

This was tested with the full results API, but it might not be required.

```json
{
"mcpServers": {
"MCP-wolfram-alpha": {
"command": "uv",
"args": [
"--directory",
"C:\\Users\\root\\Documents\\MCP-wolfram-alpha",
"run",
"MCP-wolfram-alpha"
],
"env": {
"WOLFRAM_API_KEY": "your-app-id"
}
}
}
}
```

## Development

### Debugging

Since the official MCP inspector does not have good environment support, I reccommend using wong2's [mcp-cli-inspector](https://github.com/wong2/mcp-cli).

Create a config.json file in the same style as claude desktop.

```json
{
"mcpServers": {
"MCP-wolfram-alpha": {
"command": "uv",
"args": [
"--directory",
"/full/path/to/MCP-wolfram-alpha",
"run",
"MCP-wolfram-alpha"
],
"env": {
"WOLFRAM_API_KEY": "your-app-id"
}
}
}
}
```

Then run:

```bash
npx @wong2/mcp-cli -c .\config.json
```